Overview

Dataset statistics

Number of variables62
Number of observations115
Missing cells2871
Missing cells (%)40.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory55.8 KiB
Average record size in memory497.1 B

Variable types

Numeric12
Categorical41
Unsupported9

Alerts

airdate has constant value "2020-12-24" Constant
_embedded.show.dvdCountry.name has constant value "Korea, Republic of" Constant
_embedded.show.dvdCountry.code has constant value "KR" Constant
_embedded.show.dvdCountry.timezone has constant value "Asia/Seoul" Constant
url has a high cardinality: 115 distinct values High cardinality
name has a high cardinality: 87 distinct values High cardinality
_links.self.href has a high cardinality: 115 distinct values High cardinality
_embedded.show.url has a high cardinality: 73 distinct values High cardinality
_embedded.show.name has a high cardinality: 73 distinct values High cardinality
_embedded.show.premiered has a high cardinality: 55 distinct values High cardinality
_embedded.show.officialSite has a high cardinality: 63 distinct values High cardinality
_embedded.show.image.medium has a high cardinality: 68 distinct values High cardinality
_embedded.show.image.original has a high cardinality: 68 distinct values High cardinality
_embedded.show.summary has a high cardinality: 65 distinct values High cardinality
_embedded.show._links.self.href has a high cardinality: 73 distinct values High cardinality
_embedded.show._links.previousepisode.href has a high cardinality: 73 distinct values High cardinality
id is highly correlated with rating.average and 3 other fieldsHigh correlation
season is highly correlated with _embedded.show.externals.tvrage and 2 other fieldsHigh correlation
number is highly correlated with rating.average and 2 other fieldsHigh correlation
runtime is highly correlated with rating.average and 5 other fieldsHigh correlation
rating.average is highly correlated with id and 9 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 3 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 3 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 5 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with id and 3 other fieldsHigh correlation
_embedded.show.weight is highly correlated with rating.average and 3 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with rating.average and 1 other fieldsHigh correlation
_embedded.show.externals.tvrage is highly correlated with id and 9 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 2 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with season and 7 other fieldsHigh correlation
id is highly correlated with rating.average and 2 other fieldsHigh correlation
season is highly correlated with number and 3 other fieldsHigh correlation
number is highly correlated with season and 2 other fieldsHigh correlation
runtime is highly correlated with rating.average and 5 other fieldsHigh correlation
rating.average is highly correlated with id and 6 other fieldsHigh correlation
_embedded.show.id is highly correlated with _embedded.show.weight and 3 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 3 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 5 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with id and 6 other fieldsHigh correlation
_embedded.show.weight is highly correlated with rating.average and 4 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with rating.average and 1 other fieldsHigh correlation
_embedded.show.externals.tvrage is highly correlated with id and 9 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with _embedded.show.id and 3 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with season and 9 other fieldsHigh correlation
id is highly correlated with _embedded.show.id and 1 other fieldsHigh correlation
season is highly correlated with _embedded.show.externals.tvrage and 1 other fieldsHigh correlation
number is highly correlated with _embedded.show.externals.tvrage and 1 other fieldsHigh correlation
runtime is highly correlated with rating.average and 4 other fieldsHigh correlation
rating.average is highly correlated with runtime and 3 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 1 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 3 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 5 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with rating.average and 1 other fieldsHigh correlation
_embedded.show.weight is highly correlated with _embedded.show.externals.tvrage and 1 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with rating.average and 1 other fieldsHigh correlation
_embedded.show.externals.tvrage is highly correlated with id and 9 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 1 other fieldsHigh correlation
_embedded.show.updated is highly correlated with _embedded.show.externals.tvrage and 1 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with number and 6 other fieldsHigh correlation
id is highly correlated with name and 35 other fieldsHigh correlation
name is highly correlated with id and 39 other fieldsHigh correlation
season is highly correlated with id and 21 other fieldsHigh correlation
number is highly correlated with name and 27 other fieldsHigh correlation
type is highly correlated with name and 11 other fieldsHigh correlation
airtime is highly correlated with id and 33 other fieldsHigh correlation
airstamp is highly correlated with id and 42 other fieldsHigh correlation
runtime is highly correlated with name and 34 other fieldsHigh correlation
summary is highly correlated with id and 35 other fieldsHigh correlation
rating.average is highly correlated with name and 25 other fieldsHigh correlation
image.medium is highly correlated with id and 36 other fieldsHigh correlation
image.original is highly correlated with id and 36 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 32 other fieldsHigh correlation
_embedded.show.url is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.name is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.type is highly correlated with name and 37 other fieldsHigh correlation
_embedded.show.language is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show.status is highly correlated with name and 35 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with name and 38 other fieldsHigh correlation
_embedded.show.premiered is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.ended is highly correlated with id and 33 other fieldsHigh correlation
_embedded.show.officialSite is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.schedule.time is highly correlated with name and 31 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with id and 33 other fieldsHigh correlation
_embedded.show.weight is highly correlated with id and 33 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with id and 36 other fieldsHigh correlation
_embedded.show.webChannel.name is highly correlated with id and 40 other fieldsHigh correlation
_embedded.show.webChannel.country.name is highly correlated with id and 33 other fieldsHigh correlation
_embedded.show.webChannel.country.code is highly correlated with id and 33 other fieldsHigh correlation
_embedded.show.webChannel.country.timezone is highly correlated with id and 33 other fieldsHigh correlation
_embedded.show.webChannel.officialSite is highly correlated with id and 32 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with name and 29 other fieldsHigh correlation
_embedded.show.externals.imdb is highly correlated with id and 36 other fieldsHigh correlation
_embedded.show.image.medium is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.image.original is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.summary is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.updated is highly correlated with id and 33 other fieldsHigh correlation
_embedded.show._links.self.href is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show._links.previousepisode.href is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show._links.nextepisode.href is highly correlated with id and 28 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with id and 30 other fieldsHigh correlation
_embedded.show.network.name is highly correlated with id and 30 other fieldsHigh correlation
_embedded.show.network.country.name is highly correlated with id and 30 other fieldsHigh correlation
_embedded.show.network.country.code is highly correlated with id and 30 other fieldsHigh correlation
_embedded.show.network.country.timezone is highly correlated with id and 30 other fieldsHigh correlation
number has 2 (1.7%) missing values Missing
runtime has 11 (9.6%) missing values Missing
summary has 82 (71.3%) missing values Missing
rating.average has 112 (97.4%) missing values Missing
image.medium has 78 (67.8%) missing values Missing
image.original has 78 (67.8%) missing values Missing
_embedded.show.language has 2 (1.7%) missing values Missing
_embedded.show.runtime has 44 (38.3%) missing values Missing
_embedded.show.averageRuntime has 10 (8.7%) missing values Missing
_embedded.show.ended has 54 (47.0%) missing values Missing
_embedded.show.officialSite has 19 (16.5%) missing values Missing
_embedded.show.rating.average has 102 (88.7%) missing values Missing
_embedded.show.network has 115 (100.0%) missing values Missing
_embedded.show.webChannel.country.name has 59 (51.3%) missing values Missing
_embedded.show.webChannel.country.code has 59 (51.3%) missing values Missing
_embedded.show.webChannel.country.timezone has 59 (51.3%) missing values Missing
_embedded.show.webChannel.officialSite has 51 (44.3%) missing values Missing
_embedded.show.dvdCountry has 115 (100.0%) missing values Missing
_embedded.show.externals.tvrage has 113 (98.3%) missing values Missing
_embedded.show.externals.thetvdb has 43 (37.4%) missing values Missing
_embedded.show.externals.imdb has 57 (49.6%) missing values Missing
_embedded.show.image.medium has 6 (5.2%) missing values Missing
_embedded.show.image.original has 6 (5.2%) missing values Missing
_embedded.show.summary has 10 (8.7%) missing values Missing
image has 115 (100.0%) missing values Missing
_embedded.show.webChannel.country has 115 (100.0%) missing values Missing
_embedded.show._links.nextepisode.href has 110 (95.7%) missing values Missing
_embedded.show.image has 115 (100.0%) missing values Missing
_embedded.show.network.id has 111 (96.5%) missing values Missing
_embedded.show.network.name has 111 (96.5%) missing values Missing
_embedded.show.network.country.name has 111 (96.5%) missing values Missing
_embedded.show.network.country.code has 111 (96.5%) missing values Missing
_embedded.show.network.country.timezone has 111 (96.5%) missing values Missing
_embedded.show.network.officialSite has 115 (100.0%) missing values Missing
_embedded.show.dvdCountry.name has 114 (99.1%) missing values Missing
_embedded.show.dvdCountry.code has 114 (99.1%) missing values Missing
_embedded.show.dvdCountry.timezone has 114 (99.1%) missing values Missing
_embedded.show.webChannel has 115 (100.0%) missing values Missing
url is uniformly distributed Uniform
summary is uniformly distributed Uniform
rating.average is uniformly distributed Uniform
image.medium is uniformly distributed Uniform
image.original is uniformly distributed Uniform
_links.self.href is uniformly distributed Uniform
_embedded.show.externals.tvrage is uniformly distributed Uniform
_embedded.show._links.nextepisode.href is uniformly distributed Uniform
_embedded.show.network.id is uniformly distributed Uniform
_embedded.show.network.name is uniformly distributed Uniform
_embedded.show.network.country.name is uniformly distributed Uniform
_embedded.show.network.country.code is uniformly distributed Uniform
_embedded.show.network.country.timezone is uniformly distributed Uniform
id has unique values Unique
url has unique values Unique
_links.self.href has unique values Unique
_embedded.show.genres is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.schedule.days is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.dvdCountry is an unsupported type, check if it needs cleaning or further analysis Unsupported
image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel.country is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network.officialSite is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel is an unsupported type, check if it needs cleaning or further analysis Unsupported

Reproduction

Analysis started2022-09-06 02:47:49.454162
Analysis finished2022-09-06 02:48:06.657072
Duration17.2 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct115
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2044136.522
Minimum1949912
Maximum2379932
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-05T21:48:06.725883image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1949912
5-th percentile1962244.3
Q11985633
median1992696
Q32038287.5
95-th percentile2324411.3
Maximum2379932
Range430020
Interquartile range (IQR)52654.5

Descriptive statistics

Standard deviation110506.9608
Coefficient of variation (CV)0.05406046006
Kurtosis1.836739983
Mean2044136.522
Median Absolute Deviation (MAD)15155
Skewness1.774266467
Sum235075700
Variance1.221178838 × 1010
MonotonicityNot monotonic
2022-09-05T21:48:06.842063image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19779001
 
0.9%
20053231
 
0.9%
20000661
 
0.9%
19975271
 
0.9%
19975261
 
0.9%
19884041
 
0.9%
19854781
 
0.9%
19854771
 
0.9%
20054191
 
0.9%
19787871
 
0.9%
Other values (105)105
91.3%
ValueCountFrequency (%)
19499121
0.9%
19499131
0.9%
19503681
0.9%
19507021
0.9%
19553171
0.9%
19607331
0.9%
19628921
0.9%
19639991
0.9%
19643941
0.9%
19725731
0.9%
ValueCountFrequency (%)
23799321
0.9%
23571501
0.9%
23244151
0.9%
23244141
0.9%
23244131
0.9%
23244121
0.9%
23244111
0.9%
23244101
0.9%
23103881
0.9%
22893791
0.9%

url
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct115
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
https://www.tvmaze.com/episodes/1977900/obycnaa-zensina-2x04-seria-13
 
1
https://www.tvmaze.com/episodes/2005323/laikykites-ten-5x16-kalediniai-burtai-ir-ypatingos-eglutes
 
1
https://www.tvmaze.com/episodes/2000066/ultimate-note-1x19-episode-19
 
1
https://www.tvmaze.com/episodes/1997527/the-penalty-zone-1x20-episode-20
 
1
https://www.tvmaze.com/episodes/1997526/the-penalty-zone-1x19-episode-19
 
1
Other values (110)
110 

Length

Max length145
Median length106
Mean length81.46956522
Min length58

Characters and Unicode

Total characters9369
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique115 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/episodes/1977900/obycnaa-zensina-2x04-seria-13
2nd rowhttps://www.tvmaze.com/episodes/1963999/257-pricin-ctoby-zit-2x09-seria-22
3rd rowhttps://www.tvmaze.com/episodes/1949912/smesariki-novyj-sezon-1x33-zagvozdka
4th rowhttps://www.tvmaze.com/episodes/1949913/smesariki-novyj-sezon-1x34-starinnyj-novogodnij-obycaj
5th rowhttps://www.tvmaze.com/episodes/1960733/psih-1x08-vozrozdenie

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1977900/obycnaa-zensina-2x04-seria-131
 
0.9%
https://www.tvmaze.com/episodes/2005323/laikykites-ten-5x16-kalediniai-burtai-ir-ypatingos-eglutes1
 
0.9%
https://www.tvmaze.com/episodes/2000066/ultimate-note-1x19-episode-191
 
0.9%
https://www.tvmaze.com/episodes/1997527/the-penalty-zone-1x20-episode-201
 
0.9%
https://www.tvmaze.com/episodes/1997526/the-penalty-zone-1x19-episode-191
 
0.9%
https://www.tvmaze.com/episodes/1988404/love-teenager-1x02-school-life-after-separation-with-first-class-boyfriend1
 
0.9%
https://www.tvmaze.com/episodes/1985478/you-complete-me-1x22-episode-221
 
0.9%
https://www.tvmaze.com/episodes/1985477/you-complete-me-1x21-episode-211
 
0.9%
https://www.tvmaze.com/episodes/2005419/yes-chef-1x02-omsvarmad-av-bin-pa-gotland1
 
0.9%
https://www.tvmaze.com/episodes/1978787/offgun-mommy-taste-1x10-episode-101
 
0.9%
Other values (105)105
91.3%

Length

2022-09-05T21:48:06.973906image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1977900/obycnaa-zensina-2x04-seria-131
 
0.9%
https://www.tvmaze.com/episodes/1999303/futmallscom-1x08-episode-81
 
0.9%
https://www.tvmaze.com/episodes/1949912/smesariki-novyj-sezon-1x33-zagvozdka1
 
0.9%
https://www.tvmaze.com/episodes/1949913/smesariki-novyj-sezon-1x34-starinnyj-novogodnij-obycaj1
 
0.9%
https://www.tvmaze.com/episodes/1960733/psih-1x08-vozrozdenie1
 
0.9%
https://www.tvmaze.com/episodes/1982409/volk-1x11-seria-111
 
0.9%
https://www.tvmaze.com/episodes/1982410/volk-1x12-seria-121
 
0.9%
https://www.tvmaze.com/episodes/1987502/passaziry-1x01-svetlana-i-igor1
 
0.9%
https://www.tvmaze.com/episodes/1987720/passaziry-1x02-saska1
 
0.9%
https://www.tvmaze.com/episodes/1985788/theres-a-pit-in-my-senior-martial-brothers-brain-2x10-episode-101
 
0.9%
Other values (105)105
91.3%

Most occurring characters

ValueCountFrequency (%)
e773
 
8.3%
-723
 
7.7%
s611
 
6.5%
/575
 
6.1%
t564
 
6.0%
o526
 
5.6%
i409
 
4.4%
w377
 
4.0%
a370
 
3.9%
p359
 
3.8%
Other values (30)4082
43.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6417
68.5%
Decimal Number1309
 
14.0%
Other Punctuation920
 
9.8%
Dash Punctuation723
 
7.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e773
12.0%
s611
 
9.5%
t564
 
8.8%
o526
 
8.2%
i409
 
6.4%
w377
 
5.9%
a370
 
5.8%
p359
 
5.6%
m328
 
5.1%
d280
 
4.4%
Other values (16)1820
28.4%
Decimal Number
ValueCountFrequency (%)
1260
19.9%
2209
16.0%
0186
14.2%
9174
13.3%
394
 
7.2%
494
 
7.2%
585
 
6.5%
779
 
6.0%
876
 
5.8%
652
 
4.0%
Other Punctuation
ValueCountFrequency (%)
/575
62.5%
.230
 
25.0%
:115
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-723
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin6417
68.5%
Common2952
31.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e773
12.0%
s611
 
9.5%
t564
 
8.8%
o526
 
8.2%
i409
 
6.4%
w377
 
5.9%
a370
 
5.8%
p359
 
5.6%
m328
 
5.1%
d280
 
4.4%
Other values (16)1820
28.4%
Common
ValueCountFrequency (%)
-723
24.5%
/575
19.5%
1260
 
8.8%
.230
 
7.8%
2209
 
7.1%
0186
 
6.3%
9174
 
5.9%
:115
 
3.9%
394
 
3.2%
494
 
3.2%
Other values (4)292
9.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII9369
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e773
 
8.3%
-723
 
7.7%
s611
 
6.5%
/575
 
6.1%
t564
 
6.0%
o526
 
5.6%
i409
 
4.4%
w377
 
4.0%
a370
 
3.9%
p359
 
3.8%
Other values (30)4082
43.6%

name
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct87
Distinct (%)75.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
Episode 5
 
6
Episode 3
 
5
Episode 6
 
4
Episode 2
 
4
Episode 4
 
4
Other values (82)
92 

Length

Max length98
Median length79
Mean length20.2
Min length5

Characters and Unicode

Total characters2323
Distinct characters141
Distinct categories13 ?
Distinct scripts5 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique73 ?
Unique (%)63.5%

Sample

1st rowСерия 13
2nd rowСерия 22
3rd rowЗагвоздка
4th rowСтаринный новогодний обычай
5th rowВозрождение

Common Values

ValueCountFrequency (%)
Episode 56
 
5.2%
Episode 35
 
4.3%
Episode 64
 
3.5%
Episode 24
 
3.5%
Episode 44
 
3.5%
Episode 13
 
2.6%
Episode 192
 
1.7%
Learning In The Holidays With Blippi | 1 Hour of Blippi Educational Videos For Kids2
 
1.7%
Episode 242
 
1.7%
Episode 82
 
1.7%
Other values (77)81
70.4%

Length

2022-09-05T21:48:07.095771image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
episode48
 
11.5%
the16
 
3.8%
11
 
2.6%
59
 
2.2%
37
 
1.7%
17
 
1.7%
of6
 
1.4%
confetti6
 
1.4%
46
 
1.4%
26
 
1.4%
Other values (238)294
70.7%

Most occurring characters

ValueCountFrequency (%)
301
 
13.0%
e155
 
6.7%
i131
 
5.6%
o105
 
4.5%
s100
 
4.3%
t87
 
3.7%
d75
 
3.2%
p73
 
3.1%
a69
 
3.0%
n56
 
2.4%
Other values (131)1171
50.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1552
66.8%
Space Separator301
 
13.0%
Uppercase Letter282
 
12.1%
Decimal Number111
 
4.8%
Other Punctuation49
 
2.1%
Other Letter14
 
0.6%
Dash Punctuation7
 
0.3%
Math Symbol2
 
0.1%
Initial Punctuation1
 
< 0.1%
Close Punctuation1
 
< 0.1%
Other values (3)3
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e155
 
10.0%
i131
 
8.4%
o105
 
6.8%
s100
 
6.4%
t87
 
5.6%
d75
 
4.8%
p73
 
4.7%
a69
 
4.4%
n56
 
3.6%
r56
 
3.6%
Other values (51)645
41.6%
Uppercase Letter
ValueCountFrequency (%)
E53
18.8%
T19
 
6.7%
S18
 
6.4%
C17
 
6.0%
B16
 
5.7%
К10
 
3.5%
P10
 
3.5%
W9
 
3.2%
O9
 
3.2%
С8
 
2.8%
Other values (32)113
40.1%
Decimal Number
ValueCountFrequency (%)
227
24.3%
121
18.9%
317
15.3%
512
10.8%
011
9.9%
49
 
8.1%
66
 
5.4%
73
 
2.7%
83
 
2.7%
92
 
1.8%
Other Letter
ValueCountFrequency (%)
ن3
21.4%
ا2
14.3%
و2
14.3%
ع1
 
7.1%
م1
 
7.1%
ش1
 
7.1%
ر1
 
7.1%
د1
 
7.1%
ك1
 
7.1%
1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
'14
28.6%
:11
22.4%
,9
18.4%
/5
 
10.2%
.5
 
10.2%
?2
 
4.1%
&1
 
2.0%
#1
 
2.0%
*1
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
-5
71.4%
2
 
28.6%
Space Separator
ValueCountFrequency (%)
301
100.0%
Math Symbol
ValueCountFrequency (%)
|2
100.0%
Initial Punctuation
ValueCountFrequency (%)
«1
100.0%
Close Punctuation
ValueCountFrequency (%)
)1
100.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%
Final Punctuation
ValueCountFrequency (%)
»1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1366
58.8%
Common475
 
20.4%
Cyrillic468
 
20.1%
Arabic13
 
0.6%
Han1
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e155
 
11.3%
i131
 
9.6%
o105
 
7.7%
s100
 
7.3%
t87
 
6.4%
d75
 
5.5%
p73
 
5.3%
a69
 
5.1%
n56
 
4.1%
r56
 
4.1%
Other values (43)459
33.6%
Cyrillic
ValueCountFrequency (%)
о51
 
10.9%
а43
 
9.2%
р36
 
7.7%
и29
 
6.2%
е28
 
6.0%
н24
 
5.1%
к22
 
4.7%
с20
 
4.3%
в18
 
3.8%
л14
 
3.0%
Other values (40)183
39.1%
Common
ValueCountFrequency (%)
301
63.4%
227
 
5.7%
121
 
4.4%
317
 
3.6%
'14
 
2.9%
512
 
2.5%
011
 
2.3%
:11
 
2.3%
49
 
1.9%
,9
 
1.9%
Other values (18)43
 
9.1%
Arabic
ValueCountFrequency (%)
ن3
23.1%
ا2
15.4%
و2
15.4%
ع1
 
7.7%
م1
 
7.7%
ش1
 
7.7%
ر1
 
7.7%
د1
 
7.7%
ك1
 
7.7%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1824
78.5%
Cyrillic468
 
20.1%
None14
 
0.6%
Arabic13
 
0.6%
Punctuation2
 
0.1%
CJK1
 
< 0.1%
Letterlike Symbols1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
301
16.5%
e155
 
8.5%
i131
 
7.2%
o105
 
5.8%
s100
 
5.5%
t87
 
4.8%
d75
 
4.1%
p73
 
4.0%
a69
 
3.8%
n56
 
3.1%
Other values (61)672
36.8%
Cyrillic
ValueCountFrequency (%)
о51
 
10.9%
а43
 
9.2%
р36
 
7.7%
и29
 
6.2%
е28
 
6.0%
н24
 
5.1%
к22
 
4.7%
с20
 
4.3%
в18
 
3.8%
л14
 
3.0%
Other values (40)183
39.1%
Arabic
ValueCountFrequency (%)
ن3
23.1%
ا2
15.4%
و2
15.4%
ع1
 
7.7%
م1
 
7.7%
ش1
 
7.7%
ر1
 
7.7%
د1
 
7.7%
ك1
 
7.7%
None
ValueCountFrequency (%)
ö3
21.4%
ü3
21.4%
ė2
14.3%
å2
14.3%
«1
 
7.1%
ä1
 
7.1%
ã1
 
7.1%
»1
 
7.1%
Punctuation
ValueCountFrequency (%)
2
100.0%
CJK
ValueCountFrequency (%)
1
100.0%
Letterlike Symbols
ValueCountFrequency (%)
1
100.0%

season
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct13
Distinct (%)11.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean108.0086957
Minimum1
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-05T21:48:07.186608image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32.5
95-th percentile641.7
Maximum2020
Range2019
Interquartile range (IQR)1.5

Descriptive statistics

Standard deviation450.5891172
Coefficient of variation (CV)4.171785563
Kurtosis14.90812086
Mean108.0086957
Median Absolute Deviation (MAD)0
Skewness4.079927175
Sum12421
Variance203030.5526
MonotonicityNot monotonic
2022-09-05T21:48:07.275446image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
168
59.1%
218
 
15.7%
38
 
7.0%
20206
 
5.2%
45
 
4.3%
53
 
2.6%
81
 
0.9%
61
 
0.9%
181
 
0.9%
151
 
0.9%
Other values (3)3
 
2.6%
ValueCountFrequency (%)
168
59.1%
218
 
15.7%
38
 
7.0%
45
 
4.3%
53
 
2.6%
61
 
0.9%
81
 
0.9%
91
 
0.9%
151
 
0.9%
181
 
0.9%
ValueCountFrequency (%)
20206
5.2%
511
 
0.9%
311
 
0.9%
181
 
0.9%
151
 
0.9%
91
 
0.9%
81
 
0.9%
61
 
0.9%
53
2.6%
45
4.3%

number
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct39
Distinct (%)34.5%
Missing2
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean17.18584071
Minimum1
Maximum351
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-05T21:48:07.375316image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median7
Q319
95-th percentile54.4
Maximum351
Range350
Interquartile range (IQR)15

Descriptive statistics

Standard deviation35.87392325
Coefficient of variation (CV)2.0874116
Kurtosis67.83244191
Mean17.18584071
Median Absolute Deviation (MAD)5
Skewness7.480001633
Sum1942
Variance1286.938369
MonotonicityNot monotonic
2022-09-05T21:48:07.490862image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
211
 
9.6%
59
 
7.8%
39
 
7.8%
18
 
7.0%
48
 
7.0%
87
 
6.1%
77
 
6.1%
65
 
4.3%
114
 
3.5%
104
 
3.5%
Other values (29)41
35.7%
ValueCountFrequency (%)
18
7.0%
211
9.6%
39
7.8%
48
7.0%
59
7.8%
65
4.3%
77
6.1%
87
6.1%
92
 
1.7%
104
 
3.5%
ValueCountFrequency (%)
3511
0.9%
851
0.9%
731
0.9%
681
0.9%
571
0.9%
551
0.9%
541
0.9%
522
1.7%
491
0.9%
431
0.9%

type
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
regular
113 
insignificant_special
 
1
significant_special
 
1

Length

Max length21
Median length7
Mean length7.226086957
Min length7

Characters and Unicode

Total characters831
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)1.7%

Sample

1st rowregular
2nd rowregular
3rd rowregular
4th rowregular
5th rowregular

Common Values

ValueCountFrequency (%)
regular113
98.3%
insignificant_special1
 
0.9%
significant_special1
 
0.9%

Length

2022-09-05T21:48:07.588244image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:48:07.670236image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
regular113
98.3%
insignificant_special1
 
0.9%
significant_special1
 
0.9%

Most occurring characters

ValueCountFrequency (%)
r226
27.2%
a117
14.1%
e115
13.8%
g115
13.8%
l115
13.8%
u113
13.6%
i9
 
1.1%
n5
 
0.6%
s4
 
0.5%
c4
 
0.5%
Other values (4)8
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter829
99.8%
Connector Punctuation2
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r226
27.3%
a117
14.1%
e115
13.9%
g115
13.9%
l115
13.9%
u113
13.6%
i9
 
1.1%
n5
 
0.6%
s4
 
0.5%
c4
 
0.5%
Other values (3)6
 
0.7%
Connector Punctuation
ValueCountFrequency (%)
_2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin829
99.8%
Common2
 
0.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
r226
27.3%
a117
14.1%
e115
13.9%
g115
13.9%
l115
13.9%
u113
13.6%
i9
 
1.1%
n5
 
0.6%
s4
 
0.5%
c4
 
0.5%
Other values (3)6
 
0.7%
Common
ValueCountFrequency (%)
_2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII831
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r226
27.2%
a117
14.1%
e115
13.8%
g115
13.8%
l115
13.8%
u113
13.6%
i9
 
1.1%
n5
 
0.6%
s4
 
0.5%
c4
 
0.5%
Other values (4)8
 
1.0%

airdate
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2020-12-24
115 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters1150
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-24
2nd row2020-12-24
3rd row2020-12-24
4th row2020-12-24
5th row2020-12-24

Common Values

ValueCountFrequency (%)
2020-12-24115
100.0%

Length

2022-09-05T21:48:07.744529image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:48:07.820742image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-24115
100.0%

Most occurring characters

ValueCountFrequency (%)
2460
40.0%
0230
20.0%
-230
20.0%
1115
 
10.0%
4115
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number920
80.0%
Dash Punctuation230
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2460
50.0%
0230
25.0%
1115
 
12.5%
4115
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-230
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1150
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2460
40.0%
0230
20.0%
-230
20.0%
1115
 
10.0%
4115
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1150
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2460
40.0%
0230
20.0%
-230
20.0%
1115
 
10.0%
4115
 
10.0%

airtime
Categorical

HIGH CORRELATION

Distinct13
Distinct (%)11.3%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
88 
12:00
10 
20:00
 
4
06:00
 
3
10:00
 
2
Other values (8)
 
8

Length

Max length5
Median length0
Mean length1.173913043
Min length0

Characters and Unicode

Total characters135
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)7.0%

Sample

1st row10:00
2nd row
3rd row
4th row
5th row12:00

Common Values

ValueCountFrequency (%)
88
76.5%
12:0010
 
8.7%
20:004
 
3.5%
06:003
 
2.6%
10:002
 
1.7%
11:001
 
0.9%
17:001
 
0.9%
20:201
 
0.9%
18:001
 
0.9%
19:001
 
0.9%
Other values (3)3
 
2.6%

Length

2022-09-05T21:48:07.897371image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
12:0010
37.0%
20:004
 
14.8%
06:003
 
11.1%
10:002
 
7.4%
11:001
 
3.7%
17:001
 
3.7%
20:201
 
3.7%
18:001
 
3.7%
19:001
 
3.7%
20:451
 
3.7%
Other values (2)2
 
7.4%

Most occurring characters

ValueCountFrequency (%)
063
46.7%
:27
20.0%
118
 
13.3%
217
 
12.6%
63
 
2.2%
92
 
1.5%
52
 
1.5%
71
 
0.7%
81
 
0.7%
41
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number108
80.0%
Other Punctuation27
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
063
58.3%
118
 
16.7%
217
 
15.7%
63
 
2.8%
92
 
1.9%
52
 
1.9%
71
 
0.9%
81
 
0.9%
41
 
0.9%
Other Punctuation
ValueCountFrequency (%)
:27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common135
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
063
46.7%
:27
20.0%
118
 
13.3%
217
 
12.6%
63
 
2.2%
92
 
1.5%
52
 
1.5%
71
 
0.7%
81
 
0.7%
41
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII135
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
063
46.7%
:27
20.0%
118
 
13.3%
217
 
12.6%
63
 
2.2%
92
 
1.5%
52
 
1.5%
71
 
0.7%
81
 
0.7%
41
 
0.7%

airstamp
Categorical

HIGH CORRELATION

Distinct18
Distinct (%)15.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2020-12-24T12:00:00+00:00
35 
2020-12-24T04:00:00+00:00
24 
2020-12-24T06:30:00+00:00
14 
2020-12-24T17:00:00+00:00
2020-12-24T00:00:00+00:00
Other values (13)
25 

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters2875
Distinct characters14
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)5.2%

Sample

1st row2020-12-23T22:00:00+00:00
2nd row2020-12-24T00:00:00+00:00
3rd row2020-12-24T00:00:00+00:00
4th row2020-12-24T00:00:00+00:00
5th row2020-12-24T00:00:00+00:00

Common Values

ValueCountFrequency (%)
2020-12-24T12:00:00+00:0035
30.4%
2020-12-24T04:00:00+00:0024
20.9%
2020-12-24T06:30:00+00:0014
 
12.2%
2020-12-24T17:00:00+00:009
 
7.8%
2020-12-24T00:00:00+00:008
 
7.0%
2020-12-24T09:00:00+00:005
 
4.3%
2020-12-24T03:00:00+00:003
 
2.6%
2020-12-24T05:00:00+00:003
 
2.6%
2020-12-24T10:00:00+00:002
 
1.7%
2020-12-24T08:00:00+00:002
 
1.7%
Other values (8)10
 
8.7%

Length

2022-09-05T21:48:07.993888image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-24t12:00:00+00:0035
30.4%
2020-12-24t04:00:00+00:0024
20.9%
2020-12-24t06:30:00+00:0014
 
12.2%
2020-12-24t17:00:00+00:009
 
7.8%
2020-12-24t00:00:00+00:008
 
7.0%
2020-12-24t09:00:00+00:005
 
4.3%
2020-12-24t03:00:00+00:003
 
2.6%
2020-12-24t05:00:00+00:003
 
2.6%
2020-12-24t11:00:00+00:002
 
1.7%
2020-12-24t14:00:00+00:002
 
1.7%
Other values (8)10
 
8.7%

Most occurring characters

ValueCountFrequency (%)
01204
41.9%
2500
17.4%
:345
 
12.0%
-230
 
8.0%
1170
 
5.9%
4141
 
4.9%
T115
 
4.0%
+115
 
4.0%
318
 
0.6%
614
 
0.5%
Other values (4)23
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number2070
72.0%
Other Punctuation345
 
12.0%
Dash Punctuation230
 
8.0%
Uppercase Letter115
 
4.0%
Math Symbol115
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
01204
58.2%
2500
24.2%
1170
 
8.2%
4141
 
6.8%
318
 
0.9%
614
 
0.7%
79
 
0.4%
96
 
0.3%
55
 
0.2%
83
 
0.1%
Other Punctuation
ValueCountFrequency (%)
:345
100.0%
Dash Punctuation
ValueCountFrequency (%)
-230
100.0%
Uppercase Letter
ValueCountFrequency (%)
T115
100.0%
Math Symbol
ValueCountFrequency (%)
+115
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common2760
96.0%
Latin115
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
01204
43.6%
2500
18.1%
:345
 
12.5%
-230
 
8.3%
1170
 
6.2%
4141
 
5.1%
+115
 
4.2%
318
 
0.7%
614
 
0.5%
79
 
0.3%
Other values (3)14
 
0.5%
Latin
ValueCountFrequency (%)
T115
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2875
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
01204
41.9%
2500
17.4%
:345
 
12.0%
-230
 
8.0%
1170
 
5.9%
4141
 
4.9%
T115
 
4.0%
+115
 
4.0%
318
 
0.6%
614
 
0.5%
Other values (4)23
 
0.8%

runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct40
Distinct (%)38.5%
Missing11
Missing (%)9.6%
Infinite0
Infinite (%)0.0%
Mean37.41346154
Minimum4
Maximum171
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-05T21:48:08.087685image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile10
Q120
median39
Q345.25
95-th percentile66.7
Maximum171
Range167
Interquartile range (IQR)25.25

Descriptive statistics

Standard deviation21.89454451
Coefficient of variation (CV)0.5852049932
Kurtosis12.1867395
Mean37.41346154
Median Absolute Deviation (MAD)11
Skewness2.160913762
Sum3891
Variance479.3710792
MonotonicityNot monotonic
2022-09-05T21:48:08.195057image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
4523
20.0%
507
 
6.1%
127
 
6.1%
207
 
6.1%
306
 
5.2%
385
 
4.3%
604
 
3.5%
103
 
2.6%
72
 
1.7%
232
 
1.7%
Other values (30)38
33.0%
(Missing)11
 
9.6%
ValueCountFrequency (%)
41
 
0.9%
62
 
1.7%
72
 
1.7%
103
2.6%
111
 
0.9%
127
6.1%
151
 
0.9%
172
 
1.7%
181
 
0.9%
207
6.1%
ValueCountFrequency (%)
1711
 
0.9%
781
 
0.9%
771
 
0.9%
731
 
0.9%
701
 
0.9%
671
 
0.9%
651
 
0.9%
604
3.5%
551
 
0.9%
542
1.7%

summary
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct33
Distinct (%)100.0%
Missing82
Missing (%)71.3%
Memory size1.0 KiB
<p>In this week's installment of "The Ready Room," host Wil Wheaton (Star Trek: The Next Generation) is joined by star Doug Jones (Captain Saru), who explains the intricacies of working in prosthetics and his thoughts on Saru's journey this season. Then, Janet Kidder (Osyraa) speaks with Wil about joining the Star Trek Universe's esteemed villains and the thrill of hijacking a Starfleet ship.</p>
 
1
<p>As Chris and Harris set out to live off the land, the Off the Cuff crew learns about a controversial mine, the history of the BWCAW and the community of Ely, MN. A Boundary Waters documentary.</p>
 
1
<p>Ely, MN will leave behind either a greener economy or a darker environment. Chris, Harris and the Off the Cuff crew explore a highly controversial mine, as well as attempt to complete their four day journey in the wild. A Boundary Waters documentary.</p>
 
1
<p>Point Roberts, WA may be sold to Canada. Chris and Harris explore a unique mapping accident and the fascinating community that came from it. A Point Roberts documentary.</p>
 
1
<p>The Nebula-75 crew are all set to make the best of a Christmas far from home, but when they cross paths with a stranded vessel a tale of treacherous trickery reveals itself...</p>
 
1
Other values (28)
28 

Length

Max length540
Median length182
Mean length215.5454545
Min length55

Characters and Unicode

Total characters7113
Distinct characters64
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)100.0%

Sample

1st row<p>Eminent lawyer Bikram Chandra's happy life takes a nosedive when his wife, Anuradha, stabs him. Cops are baffled with her, and finding a lawyer for her looks impossible.</p>
2nd row<p>Pradhan, Gauri and Madhav Mishra interview the Chandra house staff and discover new information. However, the situation worsens when Anu goes against Madhav's advice in court.</p>
3rd row<p>In jail, Anu meets Ishani who takes her under her wing. Outside, Madhav convinces Nikhat to meet Anu and manages to pass on a message to Rhea, her daughter.</p>
4th row<p>Pradhan is determined to record Rhea's statement before she meets Anu. Getting wind of this, Madhav stakes out Vijji's house. Meanwhile, Vijji gets a call from the hospital.</p>
5th row<p>Seven months have passed, and Mandira and Vijji have engaged a new hotshot prosecutor. In the meantime, Madhav and Nikhat delve into Anu's past, which sheds new light on Bikram.</p>

Common Values

ValueCountFrequency (%)
<p>In this week's installment of "The Ready Room," host Wil Wheaton (Star Trek: The Next Generation) is joined by star Doug Jones (Captain Saru), who explains the intricacies of working in prosthetics and his thoughts on Saru's journey this season. Then, Janet Kidder (Osyraa) speaks with Wil about joining the Star Trek Universe's esteemed villains and the thrill of hijacking a Starfleet ship.</p>1
 
0.9%
<p>As Chris and Harris set out to live off the land, the Off the Cuff crew learns about a controversial mine, the history of the BWCAW and the community of Ely, MN. A Boundary Waters documentary.</p>1
 
0.9%
<p>Ely, MN will leave behind either a greener economy or a darker environment. Chris, Harris and the Off the Cuff crew explore a highly controversial mine, as well as attempt to complete their four day journey in the wild. A Boundary Waters documentary.</p>1
 
0.9%
<p>Point Roberts, WA may be sold to Canada. Chris and Harris explore a unique mapping accident and the fascinating community that came from it. A Point Roberts documentary.</p>1
 
0.9%
<p>The Nebula-75 crew are all set to make the best of a Christmas far from home, but when they cross paths with a stranded vessel a tale of treacherous trickery reveals itself...</p>1
 
0.9%
<p>The events of the previous night left a sour taste in James's mouth, much to Dale's chagrin. But something's got to give.</p>1
 
0.9%
<p>Ellen introduces Omar to the family. Anderson is bothered by Tina's strange posts on the internet. Lica goes back to talking to Samantha. Keyla makes a revelation to Samuel.</p>1
 
0.9%
<p>Oscar has to distract Lucy while the Yetis prepare a surprise for her.</p>1
 
0.9%
<p>Eminent lawyer Bikram Chandra's happy life takes a nosedive when his wife, Anuradha, stabs him. Cops are baffled with her, and finding a lawyer for her looks impossible.</p>1
 
0.9%
<p>Lucy and a young yeti named Fife argue about the right way to raise a litter of baby yetis they found.</p>1
 
0.9%
Other values (23)23
 
20.0%
(Missing)82
71.3%

Length

2022-09-05T21:48:08.307673image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the79
 
6.7%
a42
 
3.6%
and40
 
3.4%
to40
 
3.4%
of27
 
2.3%
his14
 
1.2%
in12
 
1.0%
on11
 
0.9%
for10
 
0.9%
with9
 
0.8%
Other values (527)890
75.8%

Most occurring characters

ValueCountFrequency (%)
1137
16.0%
e677
 
9.5%
a497
 
7.0%
t477
 
6.7%
s406
 
5.7%
i391
 
5.5%
n386
 
5.4%
o333
 
4.7%
h318
 
4.5%
r302
 
4.2%
Other values (54)2189
30.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5319
74.8%
Space Separator1141
 
16.0%
Uppercase Letter270
 
3.8%
Other Punctuation224
 
3.1%
Math Symbol144
 
2.0%
Dash Punctuation7
 
0.1%
Close Punctuation3
 
< 0.1%
Open Punctuation3
 
< 0.1%
Decimal Number2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e677
12.7%
a497
 
9.3%
t477
 
9.0%
s406
 
7.6%
i391
 
7.4%
n386
 
7.3%
o333
 
6.3%
h318
 
6.0%
r302
 
5.7%
d189
 
3.6%
Other values (16)1343
25.2%
Uppercase Letter
ValueCountFrequency (%)
M34
 
12.6%
C20
 
7.4%
A20
 
7.4%
B19
 
7.0%
T18
 
6.7%
W16
 
5.9%
F15
 
5.6%
S15
 
5.6%
N13
 
4.8%
R13
 
4.8%
Other values (13)87
32.2%
Other Punctuation
ValueCountFrequency (%)
.81
36.2%
,77
34.4%
/36
16.1%
'21
 
9.4%
"8
 
3.6%
:1
 
0.4%
Space Separator
ValueCountFrequency (%)
1137
99.6%
 4
 
0.4%
Math Symbol
ValueCountFrequency (%)
<72
50.0%
>72
50.0%
Decimal Number
ValueCountFrequency (%)
71
50.0%
51
50.0%
Dash Punctuation
ValueCountFrequency (%)
-7
100.0%
Close Punctuation
ValueCountFrequency (%)
)3
100.0%
Open Punctuation
ValueCountFrequency (%)
(3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5589
78.6%
Common1524
 
21.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e677
12.1%
a497
 
8.9%
t477
 
8.5%
s406
 
7.3%
i391
 
7.0%
n386
 
6.9%
o333
 
6.0%
h318
 
5.7%
r302
 
5.4%
d189
 
3.4%
Other values (39)1613
28.9%
Common
ValueCountFrequency (%)
1137
74.6%
.81
 
5.3%
,77
 
5.1%
<72
 
4.7%
>72
 
4.7%
/36
 
2.4%
'21
 
1.4%
"8
 
0.5%
-7
 
0.5%
 4
 
0.3%
Other values (5)9
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII7109
99.9%
None4
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1137
16.0%
e677
 
9.5%
a497
 
7.0%
t477
 
6.7%
s406
 
5.7%
i391
 
5.5%
n386
 
5.4%
o333
 
4.7%
h318
 
4.5%
r302
 
4.2%
Other values (53)2185
30.7%
None
ValueCountFrequency (%)
 4
100.0%

rating.average
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct3
Distinct (%)100.0%
Missing112
Missing (%)97.4%
Memory size1.0 KiB
8.0
6.5
8.5

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters9
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row8.0
2nd row6.5
3rd row8.5

Common Values

ValueCountFrequency (%)
8.01
 
0.9%
6.51
 
0.9%
8.51
 
0.9%
(Missing)112
97.4%

Length

2022-09-05T21:48:08.399588image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:48:08.481975image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
8.01
33.3%
6.51
33.3%
8.51
33.3%

Most occurring characters

ValueCountFrequency (%)
.3
33.3%
82
22.2%
52
22.2%
01
 
11.1%
61
 
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number6
66.7%
Other Punctuation3
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
82
33.3%
52
33.3%
01
16.7%
61
16.7%
Other Punctuation
ValueCountFrequency (%)
.3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common9
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
.3
33.3%
82
22.2%
52
22.2%
01
 
11.1%
61
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII9
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
.3
33.3%
82
22.2%
52
22.2%
01
 
11.1%
61
 
11.1%

image.medium
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct37
Distinct (%)100.0%
Missing78
Missing (%)67.8%
Memory size1.0 KiB
https://static.tvmaze.com/uploads/images/medium_landscape/290/726674.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/290/726302.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/290/726289.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/290/726244.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/290/726333.jpg
 
1
Other values (32)
32 

Length

Max length73
Median length72
Mean length72.05405405
Min length72

Characters and Unicode

Total characters2666
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_landscape/290/726674.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/301/752694.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/375/939994.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/291/728563.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/393/983021.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/290/726674.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726302.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726289.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726244.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726333.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726494.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/290/727233.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/414/1037127.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726281.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726729.jpg1
 
0.9%
Other values (27)27
 
23.5%
(Missing)78
67.8%

Length

2022-09-05T21:48:08.559753image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/290/726674.jpg1
 
2.7%
https://static.tvmaze.com/uploads/images/medium_landscape/290/727222.jpg1
 
2.7%
https://static.tvmaze.com/uploads/images/medium_landscape/301/752694.jpg1
 
2.7%
https://static.tvmaze.com/uploads/images/medium_landscape/375/939994.jpg1
 
2.7%
https://static.tvmaze.com/uploads/images/medium_landscape/291/728563.jpg1
 
2.7%
https://static.tvmaze.com/uploads/images/medium_landscape/393/983021.jpg1
 
2.7%
https://static.tvmaze.com/uploads/images/medium_landscape/393/983052.jpg1
 
2.7%
https://static.tvmaze.com/uploads/images/medium_landscape/295/738009.jpg1
 
2.7%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726358.jpg1
 
2.7%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726377.jpg1
 
2.7%
Other values (27)27
73.0%

Most occurring characters

ValueCountFrequency (%)
/259
 
9.7%
a222
 
8.3%
t185
 
6.9%
s185
 
6.9%
m185
 
6.9%
p148
 
5.6%
e148
 
5.6%
i111
 
4.2%
c111
 
4.2%
.111
 
4.2%
Other values (22)1001
37.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1887
70.8%
Other Punctuation407
 
15.3%
Decimal Number335
 
12.6%
Connector Punctuation37
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a222
11.8%
t185
9.8%
s185
9.8%
m185
9.8%
p148
 
7.8%
e148
 
7.8%
i111
 
5.9%
c111
 
5.9%
d111
 
5.9%
l74
 
3.9%
Other values (8)407
21.6%
Decimal Number
ValueCountFrequency (%)
279
23.6%
950
14.9%
747
14.0%
340
11.9%
038
11.3%
631
 
9.3%
815
 
4.5%
414
 
4.2%
114
 
4.2%
57
 
2.1%
Other Punctuation
ValueCountFrequency (%)
/259
63.6%
.111
27.3%
:37
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1887
70.8%
Common779
29.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a222
11.8%
t185
9.8%
s185
9.8%
m185
9.8%
p148
 
7.8%
e148
 
7.8%
i111
 
5.9%
c111
 
5.9%
d111
 
5.9%
l74
 
3.9%
Other values (8)407
21.6%
Common
ValueCountFrequency (%)
/259
33.2%
.111
14.2%
279
 
10.1%
950
 
6.4%
747
 
6.0%
340
 
5.1%
038
 
4.9%
_37
 
4.7%
:37
 
4.7%
631
 
4.0%
Other values (4)50
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII2666
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/259
 
9.7%
a222
 
8.3%
t185
 
6.9%
s185
 
6.9%
m185
 
6.9%
p148
 
5.6%
e148
 
5.6%
i111
 
4.2%
c111
 
4.2%
.111
 
4.2%
Other values (22)1001
37.5%

image.original
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct37
Distinct (%)100.0%
Missing78
Missing (%)67.8%
Memory size1.0 KiB
https://static.tvmaze.com/uploads/images/original_untouched/290/726674.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/290/726302.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/290/726289.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/290/726244.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/290/726333.jpg
 
1
Other values (32)
32 

Length

Max length75
Median length74
Mean length74.05405405
Min length74

Characters and Unicode

Total characters2740
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/290/726674.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/301/752694.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/375/939994.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/291/728563.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/393/983021.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/290/726674.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/290/726302.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/290/726289.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/290/726244.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/290/726333.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/290/726494.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/290/727233.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/414/1037127.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/290/726281.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/290/726729.jpg1
 
0.9%
Other values (27)27
 
23.5%
(Missing)78
67.8%

Length

2022-09-05T21:48:08.645211image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/290/726674.jpg1
 
2.7%
https://static.tvmaze.com/uploads/images/original_untouched/290/727222.jpg1
 
2.7%
https://static.tvmaze.com/uploads/images/original_untouched/301/752694.jpg1
 
2.7%
https://static.tvmaze.com/uploads/images/original_untouched/375/939994.jpg1
 
2.7%
https://static.tvmaze.com/uploads/images/original_untouched/291/728563.jpg1
 
2.7%
https://static.tvmaze.com/uploads/images/original_untouched/393/983021.jpg1
 
2.7%
https://static.tvmaze.com/uploads/images/original_untouched/393/983052.jpg1
 
2.7%
https://static.tvmaze.com/uploads/images/original_untouched/295/738009.jpg1
 
2.7%
https://static.tvmaze.com/uploads/images/original_untouched/290/726358.jpg1
 
2.7%
https://static.tvmaze.com/uploads/images/original_untouched/290/726377.jpg1
 
2.7%
Other values (27)27
73.0%

Most occurring characters

ValueCountFrequency (%)
/259
 
9.5%
t222
 
8.1%
a185
 
6.8%
s148
 
5.4%
o148
 
5.4%
i148
 
5.4%
m111
 
4.1%
u111
 
4.1%
e111
 
4.1%
g111
 
4.1%
Other values (23)1186
43.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1961
71.6%
Other Punctuation407
 
14.9%
Decimal Number335
 
12.2%
Connector Punctuation37
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t222
 
11.3%
a185
 
9.4%
s148
 
7.5%
o148
 
7.5%
i148
 
7.5%
m111
 
5.7%
u111
 
5.7%
e111
 
5.7%
g111
 
5.7%
c111
 
5.7%
Other values (9)555
28.3%
Decimal Number
ValueCountFrequency (%)
279
23.6%
950
14.9%
747
14.0%
340
11.9%
038
11.3%
631
 
9.3%
815
 
4.5%
414
 
4.2%
114
 
4.2%
57
 
2.1%
Other Punctuation
ValueCountFrequency (%)
/259
63.6%
.111
27.3%
:37
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1961
71.6%
Common779
 
28.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t222
 
11.3%
a185
 
9.4%
s148
 
7.5%
o148
 
7.5%
i148
 
7.5%
m111
 
5.7%
u111
 
5.7%
e111
 
5.7%
g111
 
5.7%
c111
 
5.7%
Other values (9)555
28.3%
Common
ValueCountFrequency (%)
/259
33.2%
.111
14.2%
279
 
10.1%
950
 
6.4%
747
 
6.0%
340
 
5.1%
038
 
4.9%
_37
 
4.7%
:37
 
4.7%
631
 
4.0%
Other values (4)50
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII2740
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/259
 
9.5%
t222
 
8.1%
a185
 
6.8%
s148
 
5.4%
o148
 
5.4%
i148
 
5.4%
m111
 
4.1%
u111
 
4.1%
e111
 
4.1%
g111
 
4.1%
Other values (23)1186
43.3%

_links.self.href
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct115
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
https://api.tvmaze.com/episodes/1977900
 
1
https://api.tvmaze.com/episodes/2005323
 
1
https://api.tvmaze.com/episodes/2000066
 
1
https://api.tvmaze.com/episodes/1997527
 
1
https://api.tvmaze.com/episodes/1997526
 
1
Other values (110)
110 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters4485
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique115 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/1977900
2nd rowhttps://api.tvmaze.com/episodes/1963999
3rd rowhttps://api.tvmaze.com/episodes/1949912
4th rowhttps://api.tvmaze.com/episodes/1949913
5th rowhttps://api.tvmaze.com/episodes/1960733

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19779001
 
0.9%
https://api.tvmaze.com/episodes/20053231
 
0.9%
https://api.tvmaze.com/episodes/20000661
 
0.9%
https://api.tvmaze.com/episodes/19975271
 
0.9%
https://api.tvmaze.com/episodes/19975261
 
0.9%
https://api.tvmaze.com/episodes/19884041
 
0.9%
https://api.tvmaze.com/episodes/19854781
 
0.9%
https://api.tvmaze.com/episodes/19854771
 
0.9%
https://api.tvmaze.com/episodes/20054191
 
0.9%
https://api.tvmaze.com/episodes/19787871
 
0.9%
Other values (105)105
91.3%

Length

2022-09-05T21:48:08.730575image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19779001
 
0.9%
https://api.tvmaze.com/episodes/19993031
 
0.9%
https://api.tvmaze.com/episodes/19499121
 
0.9%
https://api.tvmaze.com/episodes/19499131
 
0.9%
https://api.tvmaze.com/episodes/19607331
 
0.9%
https://api.tvmaze.com/episodes/19824091
 
0.9%
https://api.tvmaze.com/episodes/19824101
 
0.9%
https://api.tvmaze.com/episodes/19875021
 
0.9%
https://api.tvmaze.com/episodes/19877201
 
0.9%
https://api.tvmaze.com/episodes/19857881
 
0.9%
Other values (105)105
91.3%

Most occurring characters

ValueCountFrequency (%)
/460
 
10.3%
p345
 
7.7%
s345
 
7.7%
e345
 
7.7%
t345
 
7.7%
o230
 
5.1%
a230
 
5.1%
i230
 
5.1%
.230
 
5.1%
m230
 
5.1%
Other values (16)1495
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2875
64.1%
Other Punctuation805
 
17.9%
Decimal Number805
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p345
12.0%
s345
12.0%
e345
12.0%
t345
12.0%
o230
8.0%
a230
8.0%
i230
8.0%
m230
8.0%
h115
 
4.0%
d115
 
4.0%
Other values (3)345
12.0%
Decimal Number
ValueCountFrequency (%)
9165
20.5%
1128
15.9%
2105
13.0%
087
10.8%
764
 
8.0%
860
 
7.5%
460
 
7.5%
552
 
6.5%
348
 
6.0%
636
 
4.5%
Other Punctuation
ValueCountFrequency (%)
/460
57.1%
.230
28.6%
:115
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2875
64.1%
Common1610
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/460
28.6%
.230
14.3%
9165
 
10.2%
1128
 
8.0%
:115
 
7.1%
2105
 
6.5%
087
 
5.4%
764
 
4.0%
860
 
3.7%
460
 
3.7%
Other values (3)136
 
8.4%
Latin
ValueCountFrequency (%)
p345
12.0%
s345
12.0%
e345
12.0%
t345
12.0%
o230
8.0%
a230
8.0%
i230
8.0%
m230
8.0%
h115
 
4.0%
d115
 
4.0%
Other values (3)345
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII4485
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/460
 
10.3%
p345
 
7.7%
s345
 
7.7%
e345
 
7.7%
t345
 
7.7%
o230
 
5.1%
a230
 
5.1%
i230
 
5.1%
.230
 
5.1%
m230
 
5.1%
Other values (16)1495
33.3%

_embedded.show.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct73
Distinct (%)63.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47985.63478
Minimum2504
Maximum63719
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-05T21:48:08.835701image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum2504
5-th percentile26643
Q145526
median52499
Q352802.5
95-th percentile58860.6
Maximum63719
Range61215
Interquartile range (IQR)7276.5

Descriptive statistics

Standard deviation10839.31732
Coefficient of variation (CV)0.2258867131
Kurtosis5.302641674
Mean47985.63478
Median Absolute Deviation (MAD)2335
Skewness-2.132718675
Sum5518348
Variance117490799.9
MonotonicityNot monotonic
2022-09-05T21:48:08.958997image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
526098
 
7.0%
526106
 
5.2%
527846
 
5.2%
414906
 
5.2%
266435
 
4.3%
533193
 
2.6%
498432
 
1.7%
551992
 
1.7%
586892
 
1.7%
528062
 
1.7%
Other values (63)73
63.5%
ValueCountFrequency (%)
25041
 
0.9%
65441
 
0.9%
74801
 
0.9%
167531
 
0.9%
266435
4.3%
283811
 
0.9%
306061
 
0.9%
357901
 
0.9%
380311
 
0.9%
390531
 
0.9%
ValueCountFrequency (%)
637191
0.9%
629011
0.9%
608482
1.7%
600861
0.9%
592611
0.9%
586892
1.7%
583671
0.9%
575561
0.9%
566051
0.9%
562531
0.9%

_embedded.show.url
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct73
Distinct (%)63.5%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
https://www.tvmaze.com/shows/52609/criminal-justice-behind-closed-doors
 
8
https://www.tvmaze.com/shows/52610/feluda-pherot
 
6
https://www.tvmaze.com/shows/52784/unique-lady-2
 
6
https://www.tvmaze.com/shows/41490/unique-lady
 
6
https://www.tvmaze.com/shows/26643/summer-camp-island
 
5
Other values (68)
84 

Length

Max length83
Median length59
Mean length50.44347826
Min length39

Characters and Unicode

Total characters5801
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)46.1%

Sample

1st rowhttps://www.tvmaze.com/shows/39115/obycnaa-zensina
2nd rowhttps://www.tvmaze.com/shows/43722/257-pricin-ctoby-zit
3rd rowhttps://www.tvmaze.com/shows/48151/smesariki-novyj-sezon
4th rowhttps://www.tvmaze.com/shows/48151/smesariki-novyj-sezon
5th rowhttps://www.tvmaze.com/shows/49280/psih

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/shows/52609/criminal-justice-behind-closed-doors8
 
7.0%
https://www.tvmaze.com/shows/52610/feluda-pherot6
 
5.2%
https://www.tvmaze.com/shows/52784/unique-lady-26
 
5.2%
https://www.tvmaze.com/shows/41490/unique-lady6
 
5.2%
https://www.tvmaze.com/shows/26643/summer-camp-island5
 
4.3%
https://www.tvmaze.com/shows/53319/off-the-cuff3
 
2.6%
https://www.tvmaze.com/shows/49843/aile-sirketi2
 
1.7%
https://www.tvmaze.com/shows/55199/klassen2
 
1.7%
https://www.tvmaze.com/shows/58689/my-supernatural-power2
 
1.7%
https://www.tvmaze.com/shows/52806/ultimate-note2
 
1.7%
Other values (63)73
63.5%

Length

2022-09-05T21:48:09.066664image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/shows/52609/criminal-justice-behind-closed-doors8
 
7.0%
https://www.tvmaze.com/shows/52784/unique-lady-26
 
5.2%
https://www.tvmaze.com/shows/41490/unique-lady6
 
5.2%
https://www.tvmaze.com/shows/52610/feluda-pherot6
 
5.2%
https://www.tvmaze.com/shows/26643/summer-camp-island5
 
4.3%
https://www.tvmaze.com/shows/53319/off-the-cuff3
 
2.6%
https://www.tvmaze.com/shows/52421/you-complete-me2
 
1.7%
https://www.tvmaze.com/shows/60848/blippi2
 
1.7%
https://www.tvmaze.com/shows/47912/the-wolf2
 
1.7%
https://www.tvmaze.com/shows/53830/witches2
 
1.7%
Other values (63)73
63.5%

Most occurring characters

ValueCountFrequency (%)
/575
 
9.9%
w478
 
8.2%
s457
 
7.9%
t443
 
7.6%
o352
 
6.1%
e298
 
5.1%
m291
 
5.0%
h274
 
4.7%
a231
 
4.0%
.230
 
4.0%
Other values (30)2172
37.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4104
70.7%
Other Punctuation920
 
15.9%
Decimal Number588
 
10.1%
Dash Punctuation189
 
3.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w478
11.6%
s457
11.1%
t443
10.8%
o352
 
8.6%
e298
 
7.3%
m291
 
7.1%
h274
 
6.7%
a231
 
5.6%
c172
 
4.2%
p151
 
3.7%
Other values (16)957
23.3%
Decimal Number
ValueCountFrequency (%)
593
15.8%
275
12.8%
470
11.9%
663
10.7%
958
9.9%
056
9.5%
152
8.8%
849
8.3%
342
7.1%
730
 
5.1%
Other Punctuation
ValueCountFrequency (%)
/575
62.5%
.230
 
25.0%
:115
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-189
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4104
70.7%
Common1697
29.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
w478
11.6%
s457
11.1%
t443
10.8%
o352
 
8.6%
e298
 
7.3%
m291
 
7.1%
h274
 
6.7%
a231
 
5.6%
c172
 
4.2%
p151
 
3.7%
Other values (16)957
23.3%
Common
ValueCountFrequency (%)
/575
33.9%
.230
 
13.6%
-189
 
11.1%
:115
 
6.8%
593
 
5.5%
275
 
4.4%
470
 
4.1%
663
 
3.7%
958
 
3.4%
056
 
3.3%
Other values (4)173
 
10.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII5801
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/575
 
9.9%
w478
 
8.2%
s457
 
7.9%
t443
 
7.6%
o352
 
6.1%
e298
 
5.1%
m291
 
5.0%
h274
 
4.7%
a231
 
4.0%
.230
 
4.0%
Other values (30)2172
37.4%

_embedded.show.name
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct73
Distinct (%)63.5%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
Criminal Justice: Behind Closed Doors
 
8
Feluda Pherot
 
6
Unique Lady 2
 
6
Unique Lady
 
6
Summer Camp Island
 
5
Other values (68)
84 

Length

Max length50
Median length28
Mean length15.73913043
Min length4

Characters and Unicode

Total characters1810
Distinct characters109
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)46.1%

Sample

1st rowОбычная женщина
2nd row257 причин, чтобы жить
3rd rowСмешарики. Новый сезон
4th rowСмешарики. Новый сезон
5th rowПсих

Common Values

ValueCountFrequency (%)
Criminal Justice: Behind Closed Doors8
 
7.0%
Feluda Pherot6
 
5.2%
Unique Lady 26
 
5.2%
Unique Lady6
 
5.2%
Summer Camp Island5
 
4.3%
Off the Cuff3
 
2.6%
Aile Şirketi2
 
1.7%
Klassen2
 
1.7%
My Supernatural Power2
 
1.7%
Ultimate Note2
 
1.7%
Other values (63)73
63.5%

Length

2022-09-05T21:48:09.170813image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
lady12
 
3.9%
the12
 
3.9%
unique12
 
3.9%
doors8
 
2.6%
criminal8
 
2.6%
closed8
 
2.6%
behind8
 
2.6%
justice8
 
2.6%
feluda6
 
2.0%
pherot6
 
2.0%
Other values (156)216
71.1%

Most occurring characters

ValueCountFrequency (%)
189
 
10.4%
e167
 
9.2%
a92
 
5.1%
o92
 
5.1%
i91
 
5.0%
n77
 
4.3%
r72
 
4.0%
t69
 
3.8%
s68
 
3.8%
l63
 
3.5%
Other values (99)830
45.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1298
71.7%
Uppercase Letter279
 
15.4%
Space Separator189
 
10.4%
Other Punctuation27
 
1.5%
Decimal Number16
 
0.9%
Dash Punctuation1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e167
 
12.9%
a92
 
7.1%
o92
 
7.1%
i91
 
7.0%
n77
 
5.9%
r72
 
5.5%
t69
 
5.3%
s68
 
5.2%
l63
 
4.9%
u56
 
4.3%
Other values (49)451
34.7%
Uppercase Letter
ValueCountFrequency (%)
C28
 
10.0%
S27
 
9.7%
T24
 
8.6%
L23
 
8.2%
U16
 
5.7%
M16
 
5.7%
B15
 
5.4%
P12
 
4.3%
D11
 
3.9%
J10
 
3.6%
Other values (26)97
34.8%
Other Punctuation
ValueCountFrequency (%)
:11
40.7%
'5
18.5%
.4
 
14.8%
,3
 
11.1%
!2
 
7.4%
&1
 
3.7%
?1
 
3.7%
Decimal Number
ValueCountFrequency (%)
29
56.2%
02
 
12.5%
52
 
12.5%
72
 
12.5%
61
 
6.2%
Space Separator
ValueCountFrequency (%)
189
100.0%
Dash Punctuation
ValueCountFrequency (%)
-1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1401
77.4%
Common233
 
12.9%
Cyrillic176
 
9.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e167
 
11.9%
a92
 
6.6%
o92
 
6.6%
i91
 
6.5%
n77
 
5.5%
r72
 
5.1%
t69
 
4.9%
s68
 
4.9%
l63
 
4.5%
u56
 
4.0%
Other values (47)554
39.5%
Cyrillic
ValueCountFrequency (%)
о21
 
11.9%
и13
 
7.4%
р12
 
6.8%
а12
 
6.8%
н11
 
6.2%
е11
 
6.2%
с8
 
4.5%
к7
 
4.0%
ы6
 
3.4%
т5
 
2.8%
Other values (28)70
39.8%
Common
ValueCountFrequency (%)
189
81.1%
:11
 
4.7%
29
 
3.9%
'5
 
2.1%
.4
 
1.7%
,3
 
1.3%
02
 
0.9%
52
 
0.9%
72
 
0.9%
!2
 
0.9%
Other values (4)4
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII1626
89.8%
Cyrillic176
 
9.7%
None8
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
189
 
11.6%
e167
 
10.3%
a92
 
5.7%
o92
 
5.7%
i91
 
5.6%
n77
 
4.7%
r72
 
4.4%
t69
 
4.2%
s68
 
4.2%
l63
 
3.9%
Other values (55)646
39.7%
Cyrillic
ValueCountFrequency (%)
о21
 
11.9%
и13
 
7.4%
р12
 
6.8%
а12
 
6.8%
н11
 
6.2%
е11
 
6.2%
с8
 
4.5%
к7
 
4.0%
ы6
 
3.4%
т5
 
2.8%
Other values (28)70
39.8%
None
ValueCountFrequency (%)
ı2
25.0%
Ş2
25.0%
Ç1
12.5%
ė1
12.5%
ğ1
12.5%
ø1
12.5%

_embedded.show.type
Categorical

HIGH CORRELATION

Distinct7
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
Scripted
75 
Animation
13 
Talk Show
12 
Documentary
 
7
Reality
 
4
Other values (2)
 
4

Length

Max length11
Median length8
Mean length8.32173913
Min length6

Characters and Unicode

Total characters957
Distinct characters25
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.9%

Sample

1st rowScripted
2nd rowScripted
3rd rowAnimation
4th rowAnimation
5th rowScripted

Common Values

ValueCountFrequency (%)
Scripted75
65.2%
Animation13
 
11.3%
Talk Show12
 
10.4%
Documentary7
 
6.1%
Reality4
 
3.5%
Variety3
 
2.6%
Sports1
 
0.9%

Length

2022-09-05T21:48:09.274044image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:48:09.372042image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
scripted75
59.1%
animation13
 
10.2%
talk12
 
9.4%
show12
 
9.4%
documentary7
 
5.5%
reality4
 
3.1%
variety3
 
2.4%
sports1
 
0.8%

Most occurring characters

ValueCountFrequency (%)
i108
11.3%
t103
10.8%
e89
9.3%
S88
9.2%
r86
9.0%
c82
8.6%
p76
7.9%
d75
7.8%
a39
 
4.1%
o33
 
3.4%
Other values (15)178
18.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter818
85.5%
Uppercase Letter127
 
13.3%
Space Separator12
 
1.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i108
13.2%
t103
12.6%
e89
10.9%
r86
10.5%
c82
10.0%
p76
9.3%
d75
9.2%
a39
 
4.8%
o33
 
4.0%
n33
 
4.0%
Other values (8)94
11.5%
Uppercase Letter
ValueCountFrequency (%)
S88
69.3%
A13
 
10.2%
T12
 
9.4%
D7
 
5.5%
R4
 
3.1%
V3
 
2.4%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin945
98.7%
Common12
 
1.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
i108
11.4%
t103
10.9%
e89
9.4%
S88
9.3%
r86
9.1%
c82
8.7%
p76
8.0%
d75
7.9%
a39
 
4.1%
o33
 
3.5%
Other values (14)166
17.6%
Common
ValueCountFrequency (%)
12
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII957
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i108
11.3%
t103
10.8%
e89
9.3%
S88
9.2%
r86
9.0%
c82
8.6%
p76
7.9%
d75
7.8%
a39
 
4.1%
o33
 
3.4%
Other values (15)178
18.6%

_embedded.show.language
Categorical

HIGH CORRELATION
MISSING

Distinct17
Distinct (%)15.0%
Missing2
Missing (%)1.7%
Memory size1.0 KiB
Chinese
31 
English
23 
Russian
16 
Korean
Hindi
Other values (12)
27 

Length

Max length10
Median length7
Mean length6.787610619
Min length4

Characters and Unicode

Total characters767
Distinct characters33
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)3.5%

Sample

1st rowRussian
2nd rowRussian
3rd rowRussian
4th rowRussian
5th rowRussian

Common Values

ValueCountFrequency (%)
Chinese31
27.0%
English23
20.0%
Russian16
13.9%
Korean8
 
7.0%
Hindi8
 
7.0%
Bengali6
 
5.2%
Norwegian3
 
2.6%
Swedish3
 
2.6%
Turkish3
 
2.6%
Tagalog2
 
1.7%
Other values (7)10
 
8.7%

Length

2022-09-05T21:48:09.463070image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
chinese31
27.4%
english23
20.4%
russian16
14.2%
korean8
 
7.1%
hindi8
 
7.1%
bengali6
 
5.3%
swedish3
 
2.7%
turkish3
 
2.7%
norwegian3
 
2.7%
tagalog2
 
1.8%
Other values (7)10
 
8.8%

Most occurring characters

ValueCountFrequency (%)
i109
14.2%
n99
12.9%
s93
12.1%
e84
11.0%
h65
8.5%
a47
 
6.1%
g37
 
4.8%
l32
 
4.2%
C31
 
4.0%
u24
 
3.1%
Other values (23)146
19.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter654
85.3%
Uppercase Letter113
 
14.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i109
16.7%
n99
15.1%
s93
14.2%
e84
12.8%
h65
9.9%
a47
7.2%
g37
 
5.7%
l32
 
4.9%
u24
 
3.7%
r18
 
2.8%
Other values (8)46
7.0%
Uppercase Letter
ValueCountFrequency (%)
C31
27.4%
E23
20.4%
R16
14.2%
H8
 
7.1%
K8
 
7.1%
T7
 
6.2%
B6
 
5.3%
N3
 
2.7%
S3
 
2.7%
D2
 
1.8%
Other values (5)6
 
5.3%

Most occurring scripts

ValueCountFrequency (%)
Latin767
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i109
14.2%
n99
12.9%
s93
12.1%
e84
11.0%
h65
8.5%
a47
 
6.1%
g37
 
4.8%
l32
 
4.2%
C31
 
4.0%
u24
 
3.1%
Other values (23)146
19.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII767
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i109
14.2%
n99
12.9%
s93
12.1%
e84
11.0%
h65
8.5%
a47
 
6.1%
g37
 
4.8%
l32
 
4.2%
C31
 
4.0%
u24
 
3.1%
Other values (23)146
19.0%

_embedded.show.genres
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size1.0 KiB

_embedded.show.status
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
Ended
61 
Running
43 
To Be Determined
11 

Length

Max length16
Median length5
Mean length6.8
Min length5

Characters and Unicode

Total characters782
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEnded
2nd rowEnded
3rd rowRunning
4th rowRunning
5th rowEnded

Common Values

ValueCountFrequency (%)
Ended61
53.0%
Running43
37.4%
To Be Determined11
 
9.6%

Length

2022-09-05T21:48:09.548794image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:48:09.633950image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
ended61
44.5%
running43
31.4%
to11
 
8.0%
be11
 
8.0%
determined11
 
8.0%

Most occurring characters

ValueCountFrequency (%)
n201
25.7%
d133
17.0%
e105
13.4%
E61
 
7.8%
i54
 
6.9%
R43
 
5.5%
u43
 
5.5%
g43
 
5.5%
22
 
2.8%
T11
 
1.4%
Other values (6)66
 
8.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter623
79.7%
Uppercase Letter137
 
17.5%
Space Separator22
 
2.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n201
32.3%
d133
21.3%
e105
16.9%
i54
 
8.7%
u43
 
6.9%
g43
 
6.9%
o11
 
1.8%
t11
 
1.8%
r11
 
1.8%
m11
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
E61
44.5%
R43
31.4%
T11
 
8.0%
B11
 
8.0%
D11
 
8.0%
Space Separator
ValueCountFrequency (%)
22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin760
97.2%
Common22
 
2.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
n201
26.4%
d133
17.5%
e105
13.8%
E61
 
8.0%
i54
 
7.1%
R43
 
5.7%
u43
 
5.7%
g43
 
5.7%
T11
 
1.4%
o11
 
1.4%
Other values (5)55
 
7.2%
Common
ValueCountFrequency (%)
22
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII782
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n201
25.7%
d133
17.0%
e105
13.4%
E61
 
7.8%
i54
 
6.9%
R43
 
5.5%
u43
 
5.5%
g43
 
5.5%
22
 
2.8%
T11
 
1.4%
Other values (6)66
 
8.4%

_embedded.show.runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct22
Distinct (%)31.0%
Missing44
Missing (%)38.3%
Infinite0
Infinite (%)0.0%
Mean36.33802817
Minimum4
Maximum62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-05T21:48:09.713361image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile9
Q120
median45
Q345
95-th percentile60
Maximum62
Range58
Interquartile range (IQR)25

Descriptive statistics

Standard deviation16.05788072
Coefficient of variation (CV)0.441902919
Kurtosis-0.8910866487
Mean36.33802817
Median Absolute Deviation (MAD)8
Skewness-0.4279592461
Sum2580
Variance257.8555332
MonotonicityNot monotonic
2022-09-05T21:48:09.805240image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
4524
20.9%
207
 
6.1%
386
 
5.2%
606
 
5.2%
305
 
4.3%
104
 
3.5%
502
 
1.7%
72
 
1.7%
512
 
1.7%
351
 
0.9%
Other values (12)12
 
10.4%
(Missing)44
38.3%
ValueCountFrequency (%)
41
 
0.9%
72
 
1.7%
81
 
0.9%
104
3.5%
121
 
0.9%
131
 
0.9%
151
 
0.9%
181
 
0.9%
207
6.1%
231
 
0.9%
ValueCountFrequency (%)
621
 
0.9%
606
 
5.2%
581
 
0.9%
531
 
0.9%
512
 
1.7%
502
 
1.7%
4524
20.9%
401
 
0.9%
386
 
5.2%
351
 
0.9%

_embedded.show.averageRuntime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct39
Distinct (%)37.1%
Missing10
Missing (%)8.7%
Infinite0
Infinite (%)0.0%
Mean35.60952381
Minimum2
Maximum77
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-05T21:48:09.909758image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile9.2
Q121
median42
Q345
95-th percentile60
Maximum77
Range75
Interquartile range (IQR)24

Descriptive statistics

Standard deviation17.53375604
Coefficient of variation (CV)0.4923895116
Kurtosis-0.865771991
Mean35.60952381
Median Absolute Deviation (MAD)14
Skewness-0.1203368927
Sum3739
Variance307.4326007
MonotonicityNot monotonic
2022-09-05T21:48:10.025800image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
4525
21.7%
5010
 
8.7%
426
 
5.2%
105
 
4.3%
115
 
4.3%
304
 
3.5%
204
 
3.5%
604
 
3.5%
273
 
2.6%
562
 
1.7%
Other values (29)37
32.2%
(Missing)10
 
8.7%
ValueCountFrequency (%)
21
 
0.9%
41
 
0.9%
72
 
1.7%
81
 
0.9%
91
 
0.9%
105
4.3%
115
4.3%
122
 
1.7%
131
 
0.9%
141
 
0.9%
ValueCountFrequency (%)
771
 
0.9%
761
 
0.9%
631
 
0.9%
622
 
1.7%
604
 
3.5%
572
 
1.7%
562
 
1.7%
531
 
0.9%
5010
8.7%
481
 
0.9%

_embedded.show.premiered
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct55
Distinct (%)47.8%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2020-12-24
24 
2019-01-17
 
6
2020-12-17
 
5
2020-12-10
 
5
2018-07-07
 
5
Other values (50)
70 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters1150
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)31.3%

Sample

1st row2018-10-29
2nd row2020-03-26
3rd row2020-05-18
4th row2020-05-18
5th row2020-11-05

Common Values

ValueCountFrequency (%)
2020-12-2424
20.9%
2019-01-176
 
5.2%
2020-12-175
 
4.3%
2020-12-105
 
4.3%
2018-07-075
 
4.3%
2020-11-263
 
2.6%
2020-12-073
 
2.6%
2019-04-303
 
2.6%
2020-12-033
 
2.6%
2020-08-063
 
2.6%
Other values (45)55
47.8%

Length

2022-09-05T21:48:10.124648image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-2424
20.9%
2019-01-176
 
5.2%
2020-12-175
 
4.3%
2020-12-105
 
4.3%
2018-07-075
 
4.3%
2020-11-263
 
2.6%
2020-12-073
 
2.6%
2019-04-303
 
2.6%
2020-12-033
 
2.6%
2020-08-063
 
2.6%
Other values (45)55
47.8%

Most occurring characters

ValueCountFrequency (%)
2289
25.1%
0284
24.7%
-230
20.0%
1182
15.8%
436
 
3.1%
730
 
2.6%
926
 
2.3%
824
 
2.1%
321
 
1.8%
620
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number920
80.0%
Dash Punctuation230
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2289
31.4%
0284
30.9%
1182
19.8%
436
 
3.9%
730
 
3.3%
926
 
2.8%
824
 
2.6%
321
 
2.3%
620
 
2.2%
58
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
-230
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1150
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2289
25.1%
0284
24.7%
-230
20.0%
1182
15.8%
436
 
3.1%
730
 
2.6%
926
 
2.3%
824
 
2.1%
321
 
1.8%
620
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII1150
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2289
25.1%
0284
24.7%
-230
20.0%
1182
15.8%
436
 
3.1%
730
 
2.6%
926
 
2.3%
824
 
2.1%
321
 
1.8%
620
 
1.7%

_embedded.show.ended
Categorical

HIGH CORRELATION
MISSING

Distinct25
Distinct (%)41.0%
Missing54
Missing (%)47.0%
Memory size1.0 KiB
2021-01-07
13 
2020-12-24
13 
2021-01-14
2020-12-30
 
2
2021-01-02
 
2
Other values (20)
27 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters610
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)21.3%

Sample

1st row2021-01-07
2nd row2021-01-21
3rd row2020-12-24
4th row2020-12-28
5th row2020-12-28

Common Values

ValueCountFrequency (%)
2021-01-0713
 
11.3%
2020-12-2413
 
11.3%
2021-01-144
 
3.5%
2020-12-302
 
1.7%
2021-01-022
 
1.7%
2021-01-092
 
1.7%
2020-12-262
 
1.7%
2021-10-072
 
1.7%
2021-01-282
 
1.7%
2021-01-042
 
1.7%
Other values (15)17
 
14.8%
(Missing)54
47.0%

Length

2022-09-05T21:48:10.208879image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2021-01-0713
21.3%
2020-12-2413
21.3%
2021-01-144
 
6.6%
2021-10-072
 
3.3%
2022-05-272
 
3.3%
2020-12-282
 
3.3%
2021-01-282
 
3.3%
2021-01-042
 
3.3%
2020-12-262
 
3.3%
2021-01-092
 
3.3%
Other values (15)17
27.9%

Most occurring characters

ValueCountFrequency (%)
2178
29.2%
0147
24.1%
-122
20.0%
1102
16.7%
422
 
3.6%
719
 
3.1%
65
 
0.8%
85
 
0.8%
54
 
0.7%
33
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number488
80.0%
Dash Punctuation122
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2178
36.5%
0147
30.1%
1102
20.9%
422
 
4.5%
719
 
3.9%
65
 
1.0%
85
 
1.0%
54
 
0.8%
33
 
0.6%
93
 
0.6%
Dash Punctuation
ValueCountFrequency (%)
-122
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common610
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2178
29.2%
0147
24.1%
-122
20.0%
1102
16.7%
422
 
3.6%
719
 
3.1%
65
 
0.8%
85
 
0.8%
54
 
0.7%
33
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII610
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2178
29.2%
0147
24.1%
-122
20.0%
1102
16.7%
422
 
3.6%
719
 
3.1%
65
 
0.8%
85
 
0.8%
54
 
0.7%
33
 
0.5%

_embedded.show.officialSite
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct63
Distinct (%)65.6%
Missing19
Missing (%)16.5%
Memory size1.0 KiB
https://www.hotstar.com/in/tv/criminal-justice-behind-closed-doors/1260049386
https://www.addatimes.com/show/feluda-pherot-web-series
 
6
http://www.iqiyi.com/a_19rrhvpyyp.html
 
6
https://play.hbomax.com/series/urn:hbo:series:GXkyDLAgeBY7CZgEAACHO
 
5
https://www.amazon.com/Off-the-Cuf/dp/B07R6PKR45
 
3
Other values (58)
68 

Length

Max length250
Median length67
Mean length54.58333333
Min length18

Characters and Unicode

Total characters5240
Distinct characters75
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)50.0%

Sample

1st rowhttps://premier.one/show/8405
2nd rowhttps://start.ru/watch/257-prichin-chtoby-zhit
3rd rowhttps://www.kinopoisk.ru/series/1379016/
4th rowhttps://www.kinopoisk.ru/series/1379016/
5th rowhttps://more.tv/psih

Common Values

ValueCountFrequency (%)
https://www.hotstar.com/in/tv/criminal-justice-behind-closed-doors/12600493868
 
7.0%
https://www.addatimes.com/show/feluda-pherot-web-series6
 
5.2%
http://www.iqiyi.com/a_19rrhvpyyp.html6
 
5.2%
https://play.hbomax.com/series/urn:hbo:series:GXkyDLAgeBY7CZgEAACHO5
 
4.3%
https://www.amazon.com/Off-the-Cuf/dp/B07R6PKR453
 
2.6%
https://www.svtplay.se/video/31148826/klassen2
 
1.7%
https://www.iqiyi.com/a_19rrhllpip.html2
 
1.7%
https://so.youku.com/search_video/q_%E9%A2%84%E6%94%AF%E6%9C%AA%E6%9D%A5?spm=a2hbt.13141534.left-title-content-wrap.5~A2
 
1.7%
https://www.iqiyi.com/lib/m_213579814.html2
 
1.7%
https://www.iqiyi.com/a_nvzsmw0tgx.html2
 
1.7%
Other values (53)58
50.4%
(Missing)19
 
16.5%

Length

2022-09-05T21:48:10.318367image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.hotstar.com/in/tv/criminal-justice-behind-closed-doors/12600493868
 
8.3%
http://www.iqiyi.com/a_19rrhvpyyp.html6
 
6.2%
https://www.addatimes.com/show/feluda-pherot-web-series6
 
6.2%
https://play.hbomax.com/series/urn:hbo:series:gxkydlageby7czgeaacho5
 
5.2%
https://www.amazon.com/off-the-cuf/dp/b07r6pkr453
 
3.1%
https://www.wavve.com/player/vod?programid=c9901_c99000000047&page=12
 
2.1%
https://www.kinopoisk.ru/series/13790162
 
2.1%
https://premier.one/show/123392
 
2.1%
https://www.beinconnect.com.tr/diziler/aile-sirketi2
 
2.1%
https://start.ru/watch/passazhiry2
 
2.1%
Other values (53)58
60.4%

Most occurring characters

ValueCountFrequency (%)
/408
 
7.8%
t367
 
7.0%
s284
 
5.4%
w245
 
4.7%
e237
 
4.5%
o227
 
4.3%
h208
 
4.0%
.205
 
3.9%
i204
 
3.9%
p181
 
3.5%
Other values (65)2674
51.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3387
64.6%
Other Punctuation802
 
15.3%
Decimal Number541
 
10.3%
Uppercase Letter375
 
7.2%
Dash Punctuation93
 
1.8%
Connector Punctuation22
 
0.4%
Math Symbol20
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t367
 
10.8%
s284
 
8.4%
w245
 
7.2%
e237
 
7.0%
o227
 
6.7%
h208
 
6.1%
i204
 
6.0%
p181
 
5.3%
a165
 
4.9%
r155
 
4.6%
Other values (16)1114
32.9%
Uppercase Letter
ValueCountFrequency (%)
A38
 
10.1%
C35
 
9.3%
P24
 
6.4%
E23
 
6.1%
B21
 
5.6%
O19
 
5.1%
D18
 
4.8%
L18
 
4.8%
R14
 
3.7%
X14
 
3.7%
Other values (16)151
40.3%
Decimal Number
ValueCountFrequency (%)
182
15.2%
064
11.8%
661
11.3%
960
11.1%
458
10.7%
349
9.1%
845
8.3%
243
7.9%
543
7.9%
736
6.7%
Other Punctuation
ValueCountFrequency (%)
/408
50.9%
.205
25.6%
:132
 
16.5%
%39
 
4.9%
?13
 
1.6%
&3
 
0.4%
#1
 
0.1%
!1
 
0.1%
Math Symbol
ValueCountFrequency (%)
=16
80.0%
~2
 
10.0%
+2
 
10.0%
Dash Punctuation
ValueCountFrequency (%)
-93
100.0%
Connector Punctuation
ValueCountFrequency (%)
_22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3762
71.8%
Common1478
 
28.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
t367
 
9.8%
s284
 
7.5%
w245
 
6.5%
e237
 
6.3%
o227
 
6.0%
h208
 
5.5%
i204
 
5.4%
p181
 
4.8%
a165
 
4.4%
r155
 
4.1%
Other values (42)1489
39.6%
Common
ValueCountFrequency (%)
/408
27.6%
.205
13.9%
:132
 
8.9%
-93
 
6.3%
182
 
5.5%
064
 
4.3%
661
 
4.1%
960
 
4.1%
458
 
3.9%
349
 
3.3%
Other values (13)266
18.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII5240
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/408
 
7.8%
t367
 
7.0%
s284
 
5.4%
w245
 
4.7%
e237
 
4.5%
o227
 
4.3%
h208
 
4.0%
.205
 
3.9%
i204
 
3.9%
p181
 
3.5%
Other values (65)2674
51.0%

_embedded.show.schedule.time
Categorical

HIGH CORRELATION

Distinct13
Distinct (%)11.3%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
93 
20:00
 
7
19:00
 
3
06:00
 
3
22:00
 
1
Other values (8)
 
8

Length

Max length5
Median length0
Mean length0.9565217391
Min length0

Characters and Unicode

Total characters110
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)7.8%

Sample

1st row22:00
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
93
80.9%
20:007
 
6.1%
19:003
 
2.6%
06:003
 
2.6%
22:001
 
0.9%
11:001
 
0.9%
12:001
 
0.9%
10:001
 
0.9%
17:001
 
0.9%
20:201
 
0.9%
Other values (3)3
 
2.6%

Length

2022-09-05T21:48:10.412915image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20:007
31.8%
19:003
13.6%
06:003
13.6%
22:001
 
4.5%
11:001
 
4.5%
12:001
 
4.5%
10:001
 
4.5%
17:001
 
4.5%
20:201
 
4.5%
18:001
 
4.5%
Other values (2)2
 
9.1%

Most occurring characters

ValueCountFrequency (%)
054
49.1%
:22
20.0%
213
 
11.8%
110
 
9.1%
93
 
2.7%
63
 
2.7%
52
 
1.8%
71
 
0.9%
81
 
0.9%
41
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number88
80.0%
Other Punctuation22
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
054
61.4%
213
 
14.8%
110
 
11.4%
93
 
3.4%
63
 
3.4%
52
 
2.3%
71
 
1.1%
81
 
1.1%
41
 
1.1%
Other Punctuation
ValueCountFrequency (%)
:22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common110
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
054
49.1%
:22
20.0%
213
 
11.8%
110
 
9.1%
93
 
2.7%
63
 
2.7%
52
 
1.8%
71
 
0.9%
81
 
0.9%
41
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII110
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
054
49.1%
:22
20.0%
213
 
11.8%
110
 
9.1%
93
 
2.7%
63
 
2.7%
52
 
1.8%
71
 
0.9%
81
 
0.9%
41
 
0.9%

_embedded.show.schedule.days
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size1.0 KiB

_embedded.show.rating.average
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct8
Distinct (%)61.5%
Missing102
Missing (%)88.7%
Infinite0
Infinite (%)0.0%
Mean6.315384615
Minimum5.3
Maximum8.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-05T21:48:10.486903image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum5.3
5-th percentile5.36
Q15.4
median5.8
Q37.5
95-th percentile7.86
Maximum8.1
Range2.8
Interquartile range (IQR)2.1

Descriptive statistics

Standard deviation1.09075368
Coefficient of variation (CV)0.1727137373
Kurtosis-1.684592123
Mean6.315384615
Median Absolute Deviation (MAD)0.4
Skewness0.5543839346
Sum82.1
Variance1.18974359
MonotonicityNot monotonic
2022-09-05T21:48:10.568008image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
5.45
 
4.3%
7.52
 
1.7%
7.71
 
0.9%
5.81
 
0.9%
8.11
 
0.9%
7.21
 
0.9%
61
 
0.9%
5.31
 
0.9%
(Missing)102
88.7%
ValueCountFrequency (%)
5.31
 
0.9%
5.45
4.3%
5.81
 
0.9%
61
 
0.9%
7.21
 
0.9%
7.52
 
1.7%
7.71
 
0.9%
8.11
 
0.9%
ValueCountFrequency (%)
8.11
 
0.9%
7.71
 
0.9%
7.52
 
1.7%
7.21
 
0.9%
61
 
0.9%
5.81
 
0.9%
5.45
4.3%
5.31
 
0.9%

_embedded.show.weight
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct42
Distinct (%)36.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.06086957
Minimum3
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-05T21:48:10.664066image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile3
Q119
median30
Q338.5
95-th percentile85
Maximum99
Range96
Interquartile range (IQR)19.5

Descriptive statistics

Standard deviation24.62429515
Coefficient of variation (CV)0.7229496916
Kurtosis0.3104276892
Mean34.06086957
Median Absolute Deviation (MAD)9
Skewness1.098625252
Sum3917
Variance606.3559115
MonotonicityNot monotonic
2022-09-05T21:48:10.777013image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
2117
 
14.8%
37
 
6.1%
356
 
5.2%
246
 
5.2%
306
 
5.2%
855
 
4.3%
145
 
4.3%
134
 
3.5%
334
 
3.5%
374
 
3.5%
Other values (32)51
44.3%
ValueCountFrequency (%)
37
6.1%
73
2.6%
82
 
1.7%
93
2.6%
134
3.5%
145
4.3%
153
2.6%
161
 
0.9%
181
 
0.9%
201
 
0.9%
ValueCountFrequency (%)
991
 
0.9%
971
 
0.9%
931
 
0.9%
871
 
0.9%
855
4.3%
831
 
0.9%
823
2.6%
781
 
0.9%
732
 
1.7%
691
 
0.9%

_embedded.show.network
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing115
Missing (%)100.0%
Memory size1.0 KiB

_embedded.show.webChannel.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct36
Distinct (%)31.6%
Missing1
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean160.8859649
Minimum3
Maximum516
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-05T21:48:10.874850image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile15
Q130
median118
Q3245
95-th percentile425
Maximum516
Range513
Interquartile range (IQR)215

Descriptive statistics

Standard deviation136.8454822
Coefficient of variation (CV)0.8505743945
Kurtosis-0.5880516494
Mean160.8859649
Median Absolute Deviation (MAD)97
Skewness0.7616826708
Sum18341
Variance18726.686
MonotonicityNot monotonic
2022-09-05T21:48:10.981379image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
2121
18.3%
6710
 
8.7%
11810
 
8.7%
1648
 
7.0%
3296
 
5.2%
4256
 
5.2%
1046
 
5.2%
1074
 
3.5%
34
 
3.5%
2453
 
2.6%
Other values (26)36
31.3%
ValueCountFrequency (%)
34
 
3.5%
121
 
0.9%
152
 
1.7%
2121
18.3%
302
 
1.7%
511
 
0.9%
6710
8.7%
881
 
0.9%
1046
 
5.2%
1074
 
3.5%
ValueCountFrequency (%)
5161
 
0.9%
4451
 
0.9%
4256
5.2%
4141
 
0.9%
4092
 
1.7%
3812
 
1.7%
3791
 
0.9%
3651
 
0.9%
3511
 
0.9%
3296
5.2%

_embedded.show.webChannel.name
Categorical

HIGH CORRELATION

Distinct36
Distinct (%)31.6%
Missing1
Missing (%)0.9%
Memory size1.0 KiB
YouTube
21 
iQIYI
10 
Youku
10 
Disney+ Hotstar
HBO Max
Other values (31)
59 

Length

Max length15
Median length12
Mean length8.01754386
Min length4

Characters and Unicode

Total characters914
Distinct characters55
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)14.9%

Sample

1st rowPremier
2nd rowStart
3rd rowКиноПоиск HD
4th rowКиноПоиск HD
5th rowmore.tv

Common Values

ValueCountFrequency (%)
YouTube21
18.3%
iQIYI10
 
8.7%
Youku10
 
8.7%
Disney+ Hotstar8
 
7.0%
HBO Max6
 
5.2%
Addatimes6
 
5.2%
Tencent QQ6
 
5.2%
Paramount+4
 
3.5%
Prime Video4
 
3.5%
Start3
 
2.6%
Other values (26)36
31.3%

Length

2022-09-05T21:48:11.081327image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
youtube21
 
13.5%
youku10
 
6.4%
iqiyi10
 
6.4%
disney8
 
5.1%
hotstar8
 
5.1%
tv7
 
4.5%
hbo6
 
3.8%
max6
 
3.8%
addatimes6
 
3.8%
tencent6
 
3.8%
Other values (36)68
43.6%

Most occurring characters

ValueCountFrequency (%)
e76
 
8.3%
u68
 
7.4%
o59
 
6.5%
a49
 
5.4%
i45
 
4.9%
T44
 
4.8%
t44
 
4.8%
42
 
4.6%
Y41
 
4.5%
r32
 
3.5%
Other values (45)414
45.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter582
63.7%
Uppercase Letter272
29.8%
Space Separator42
 
4.6%
Math Symbol15
 
1.6%
Other Punctuation2
 
0.2%
Decimal Number1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e76
13.1%
u68
11.7%
o59
10.1%
a49
 
8.4%
i45
 
7.7%
t44
 
7.6%
r32
 
5.5%
s27
 
4.6%
n27
 
4.6%
b25
 
4.3%
Other values (18)130
22.3%
Uppercase Letter
ValueCountFrequency (%)
T44
16.2%
Y41
15.1%
I24
 
8.8%
Q22
 
8.1%
V18
 
6.6%
H16
 
5.9%
P14
 
5.1%
N12
 
4.4%
B11
 
4.0%
D10
 
3.7%
Other values (13)60
22.1%
Space Separator
ValueCountFrequency (%)
42
100.0%
Math Symbol
ValueCountFrequency (%)
+15
100.0%
Other Punctuation
ValueCountFrequency (%)
.2
100.0%
Decimal Number
ValueCountFrequency (%)
21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin836
91.5%
Common60
 
6.6%
Cyrillic18
 
2.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e76
 
9.1%
u68
 
8.1%
o59
 
7.1%
a49
 
5.9%
i45
 
5.4%
T44
 
5.3%
t44
 
5.3%
Y41
 
4.9%
r32
 
3.8%
s27
 
3.2%
Other values (34)351
42.0%
Cyrillic
ValueCountFrequency (%)
и4
22.2%
о4
22.2%
К2
11.1%
н2
11.1%
П2
11.1%
с2
11.1%
к2
11.1%
Common
ValueCountFrequency (%)
42
70.0%
+15
 
25.0%
.2
 
3.3%
21
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII896
98.0%
Cyrillic18
 
2.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e76
 
8.5%
u68
 
7.6%
o59
 
6.6%
a49
 
5.5%
i45
 
5.0%
T44
 
4.9%
t44
 
4.9%
42
 
4.7%
Y41
 
4.6%
r32
 
3.6%
Other values (38)396
44.2%
Cyrillic
ValueCountFrequency (%)
и4
22.2%
о4
22.2%
К2
11.1%
н2
11.1%
П2
11.1%
с2
11.1%
к2
11.1%

_embedded.show.webChannel.country.name
Categorical

HIGH CORRELATION
MISSING

Distinct12
Distinct (%)21.4%
Missing59
Missing (%)51.3%
Memory size1.0 KiB
China
20 
Russian Federation
10 
India
Korea, Republic of
United States
Other values (7)
11 

Length

Max length25
Median length18
Mean length9.714285714
Min length5

Characters and Unicode

Total characters544
Distinct characters35
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)7.1%

Sample

1st rowRussian Federation
2nd rowRussian Federation
3rd rowRussian Federation
4th rowRussian Federation
5th rowRussian Federation

Common Values

ValueCountFrequency (%)
China20
 
17.4%
Russian Federation10
 
8.7%
India6
 
5.2%
Korea, Republic of5
 
4.3%
United States4
 
3.5%
Turkey3
 
2.6%
Norway2
 
1.7%
Sweden2
 
1.7%
Taiwan, Province of China1
 
0.9%
Malaysia1
 
0.9%
Other values (2)2
 
1.7%
(Missing)59
51.3%

Length

2022-09-05T21:48:11.183138image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
china21
25.3%
russian10
12.0%
federation10
12.0%
india6
 
7.2%
of6
 
7.2%
korea5
 
6.0%
republic5
 
6.0%
states4
 
4.8%
united4
 
4.8%
turkey3
 
3.6%
Other values (7)9
10.8%

Most occurring characters

ValueCountFrequency (%)
a65
 
11.9%
i60
 
11.0%
n56
 
10.3%
e48
 
8.8%
27
 
5.0%
s26
 
4.8%
o24
 
4.4%
d23
 
4.2%
t23
 
4.2%
r23
 
4.2%
Other values (25)169
31.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter434
79.8%
Uppercase Letter77
 
14.2%
Space Separator27
 
5.0%
Other Punctuation6
 
1.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a65
15.0%
i60
13.8%
n56
12.9%
e48
11.1%
s26
 
6.0%
o24
 
5.5%
d23
 
5.3%
t23
 
5.3%
r23
 
5.3%
h22
 
5.1%
Other values (11)64
14.7%
Uppercase Letter
ValueCountFrequency (%)
C21
27.3%
R15
19.5%
F10
13.0%
S6
 
7.8%
I6
 
7.8%
K5
 
6.5%
U4
 
5.2%
T4
 
5.2%
N3
 
3.9%
P1
 
1.3%
Other values (2)2
 
2.6%
Space Separator
ValueCountFrequency (%)
27
100.0%
Other Punctuation
ValueCountFrequency (%)
,6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin511
93.9%
Common33
 
6.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a65
12.7%
i60
11.7%
n56
 
11.0%
e48
 
9.4%
s26
 
5.1%
o24
 
4.7%
d23
 
4.5%
t23
 
4.5%
r23
 
4.5%
h22
 
4.3%
Other values (23)141
27.6%
Common
ValueCountFrequency (%)
27
81.8%
,6
 
18.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII544
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a65
 
11.9%
i60
 
11.0%
n56
 
10.3%
e48
 
8.8%
27
 
5.0%
s26
 
4.8%
o24
 
4.4%
d23
 
4.2%
t23
 
4.2%
r23
 
4.2%
Other values (25)169
31.1%

_embedded.show.webChannel.country.code
Categorical

HIGH CORRELATION
MISSING

Distinct12
Distinct (%)21.4%
Missing59
Missing (%)51.3%
Memory size1.0 KiB
CN
20 
RU
10 
IN
KR
US
Other values (7)
11 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters112
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)7.1%

Sample

1st rowRU
2nd rowRU
3rd rowRU
4th rowRU
5th rowRU

Common Values

ValueCountFrequency (%)
CN20
 
17.4%
RU10
 
8.7%
IN6
 
5.2%
KR5
 
4.3%
US4
 
3.5%
TR3
 
2.6%
NO2
 
1.7%
SE2
 
1.7%
TW1
 
0.9%
MY1
 
0.9%
Other values (2)2
 
1.7%
(Missing)59
51.3%

Length

2022-09-05T21:48:11.269435image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
cn20
35.7%
ru10
17.9%
in6
 
10.7%
kr5
 
8.9%
us4
 
7.1%
tr3
 
5.4%
no2
 
3.6%
se2
 
3.6%
tw1
 
1.8%
my1
 
1.8%
Other values (2)2
 
3.6%

Most occurring characters

ValueCountFrequency (%)
N29
25.9%
C20
17.9%
R19
17.0%
U14
12.5%
I6
 
5.4%
S6
 
5.4%
K5
 
4.5%
T4
 
3.6%
O2
 
1.8%
E2
 
1.8%
Other values (5)5
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter112
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N29
25.9%
C20
17.9%
R19
17.0%
U14
12.5%
I6
 
5.4%
S6
 
5.4%
K5
 
4.5%
T4
 
3.6%
O2
 
1.8%
E2
 
1.8%
Other values (5)5
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
Latin112
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N29
25.9%
C20
17.9%
R19
17.0%
U14
12.5%
I6
 
5.4%
S6
 
5.4%
K5
 
4.5%
T4
 
3.6%
O2
 
1.8%
E2
 
1.8%
Other values (5)5
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII112
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N29
25.9%
C20
17.9%
R19
17.0%
U14
12.5%
I6
 
5.4%
S6
 
5.4%
K5
 
4.5%
T4
 
3.6%
O2
 
1.8%
E2
 
1.8%
Other values (5)5
 
4.5%

_embedded.show.webChannel.country.timezone
Categorical

HIGH CORRELATION
MISSING

Distinct12
Distinct (%)21.4%
Missing59
Missing (%)51.3%
Memory size1.0 KiB
Asia/Shanghai
20 
Asia/Kamchatka
10 
Asia/Kolkata
Asia/Seoul
America/New_York
Other values (7)
11 

Length

Max length16
Median length15
Mean length13.19642857
Min length10

Characters and Unicode

Total characters739
Distinct characters30
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)7.1%

Sample

1st rowAsia/Kamchatka
2nd rowAsia/Kamchatka
3rd rowAsia/Kamchatka
4th rowAsia/Kamchatka
5th rowAsia/Kamchatka

Common Values

ValueCountFrequency (%)
Asia/Shanghai20
 
17.4%
Asia/Kamchatka10
 
8.7%
Asia/Kolkata6
 
5.2%
Asia/Seoul5
 
4.3%
America/New_York4
 
3.5%
Europe/Istanbul3
 
2.6%
Europe/Oslo2
 
1.7%
Europe/Stockholm2
 
1.7%
Asia/Taipei1
 
0.9%
Asia/Kuching1
 
0.9%
Other values (2)2
 
1.7%
(Missing)59
51.3%

Length

2022-09-05T21:48:11.368121image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
asia/shanghai20
35.7%
asia/kamchatka10
17.9%
asia/kolkata6
 
10.7%
asia/seoul5
 
8.9%
america/new_york4
 
7.1%
europe/istanbul3
 
5.4%
europe/oslo2
 
3.6%
europe/stockholm2
 
3.6%
asia/taipei1
 
1.8%
asia/kuching1
 
1.8%
Other values (2)2
 
3.6%

Most occurring characters

ValueCountFrequency (%)
a136
18.4%
i71
 
9.6%
/56
 
7.6%
h54
 
7.3%
A49
 
6.6%
s49
 
6.6%
o31
 
4.2%
S27
 
3.7%
n25
 
3.4%
e24
 
3.2%
Other values (20)217
29.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter563
76.2%
Uppercase Letter116
 
15.7%
Other Punctuation56
 
7.6%
Connector Punctuation4
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a136
24.2%
i71
12.6%
h54
 
9.6%
s49
 
8.7%
o31
 
5.5%
n25
 
4.4%
e24
 
4.3%
t22
 
3.9%
k22
 
3.9%
g21
 
3.7%
Other values (9)108
19.2%
Uppercase Letter
ValueCountFrequency (%)
A49
42.2%
S27
23.3%
K17
 
14.7%
E8
 
6.9%
N5
 
4.3%
Y4
 
3.4%
I3
 
2.6%
O2
 
1.7%
T1
 
0.9%
Other Punctuation
ValueCountFrequency (%)
/56
100.0%
Connector Punctuation
ValueCountFrequency (%)
_4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin679
91.9%
Common60
 
8.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a136
20.0%
i71
 
10.5%
h54
 
8.0%
A49
 
7.2%
s49
 
7.2%
o31
 
4.6%
S27
 
4.0%
n25
 
3.7%
e24
 
3.5%
t22
 
3.2%
Other values (18)191
28.1%
Common
ValueCountFrequency (%)
/56
93.3%
_4
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII739
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a136
18.4%
i71
 
9.6%
/56
 
7.6%
h54
 
7.3%
A49
 
6.6%
s49
 
6.6%
o31
 
4.2%
S27
 
3.7%
n25
 
3.4%
e24
 
3.2%
Other values (20)217
29.4%

_embedded.show.webChannel.officialSite
Categorical

HIGH CORRELATION
MISSING

Distinct14
Distinct (%)21.9%
Missing51
Missing (%)44.3%
Memory size1.0 KiB
https://www.youtube.com
21 
https://www.iq.com/
10 
https://v.qq.com/
https://www.hbomax.com/
https://www.paramountplus.com/
Other values (9)
17 

Length

Max length30
Median length26
Mean length22.515625
Min length17

Characters and Unicode

Total characters1441
Distinct characters26
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)4.7%

Sample

1st rowhttps://hd.kinopoisk.ru/
2nd rowhttps://hd.kinopoisk.ru/
3rd rowhttps://www.wavve.com/
4th rowhttps://www.wavve.com/
5th rowhttps://www.iq.com/

Common Values

ValueCountFrequency (%)
https://www.youtube.com21
18.3%
https://www.iq.com/10
 
8.7%
https://v.qq.com/6
 
5.2%
https://www.hbomax.com/6
 
5.2%
https://www.paramountplus.com/4
 
3.5%
https://www.primevideo.com4
 
3.5%
https://hd.kinopoisk.ru/2
 
1.7%
https://www.wavve.com/2
 
1.7%
https://w.mgtv.com/2
 
1.7%
https://tv.naver.com/2
 
1.7%
Other values (4)5
 
4.3%
(Missing)51
44.3%

Length

2022-09-05T21:48:11.469745image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.youtube.com21
32.8%
https://www.iq.com10
15.6%
https://v.qq.com6
 
9.4%
https://www.hbomax.com6
 
9.4%
https://www.paramountplus.com4
 
6.2%
https://www.primevideo.com4
 
6.2%
https://hd.kinopoisk.ru2
 
3.1%
https://www.wavve.com2
 
3.1%
https://w.mgtv.com2
 
3.1%
https://tv.naver.com2
 
3.1%
Other values (4)5
 
7.8%

Most occurring characters

ValueCountFrequency (%)
/167
11.6%
t161
11.2%
w158
11.0%
.128
 
8.9%
o105
 
7.3%
p81
 
5.6%
m77
 
5.3%
s74
 
5.1%
h72
 
5.0%
:64
 
4.4%
Other values (16)354
24.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1082
75.1%
Other Punctuation359
 
24.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t161
14.9%
w158
14.6%
o105
9.7%
p81
7.5%
m77
 
7.1%
s74
 
6.8%
h72
 
6.7%
c63
 
5.8%
u54
 
5.0%
e37
 
3.4%
Other values (13)200
18.5%
Other Punctuation
ValueCountFrequency (%)
/167
46.5%
.128
35.7%
:64
 
17.8%

Most occurring scripts

ValueCountFrequency (%)
Latin1082
75.1%
Common359
 
24.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
t161
14.9%
w158
14.6%
o105
9.7%
p81
7.5%
m77
 
7.1%
s74
 
6.8%
h72
 
6.7%
c63
 
5.8%
u54
 
5.0%
e37
 
3.4%
Other values (13)200
18.5%
Common
ValueCountFrequency (%)
/167
46.5%
.128
35.7%
:64
 
17.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII1441
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/167
11.6%
t161
11.2%
w158
11.0%
.128
 
8.9%
o105
 
7.3%
p81
 
5.6%
m77
 
5.3%
s74
 
5.1%
h72
 
5.0%
:64
 
4.4%
Other values (16)354
24.6%

_embedded.show.dvdCountry
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing115
Missing (%)100.0%
Memory size1.0 KiB

_embedded.show.externals.tvrage
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct2
Distinct (%)100.0%
Missing113
Missing (%)98.3%
Memory size1.0 KiB
5152.0
19056.0

Length

Max length7
Median length6.5
Mean length6.5
Min length6

Characters and Unicode

Total characters13
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row5152.0
2nd row19056.0

Common Values

ValueCountFrequency (%)
5152.01
 
0.9%
19056.01
 
0.9%
(Missing)113
98.3%

Length

2022-09-05T21:48:11.581664image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:48:11.675113image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
5152.01
50.0%
19056.01
50.0%

Most occurring characters

ValueCountFrequency (%)
53
23.1%
03
23.1%
12
15.4%
.2
15.4%
21
 
7.7%
91
 
7.7%
61
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number11
84.6%
Other Punctuation2
 
15.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
53
27.3%
03
27.3%
12
18.2%
21
 
9.1%
91
 
9.1%
61
 
9.1%
Other Punctuation
ValueCountFrequency (%)
.2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common13
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
53
23.1%
03
23.1%
12
15.4%
.2
15.4%
21
 
7.7%
91
 
7.7%
61
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII13
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
53
23.1%
03
23.1%
12
15.4%
.2
15.4%
21
 
7.7%
91
 
7.7%
61
 
7.7%

_embedded.show.externals.thetvdb
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct50
Distinct (%)69.4%
Missing43
Missing (%)37.4%
Infinite0
Infinite (%)0.0%
Mean358977.7778
Minimum78419
Maximum394090
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-05T21:48:11.779525image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum78419
5-th percentile282487.9
Q1344750
median372332.5
Q3392410
95-th percentile394072
Maximum394090
Range315671
Interquartile range (IQR)47660

Descriptive statistics

Standard deviation54373.10813
Coefficient of variation (CV)0.1514665015
Kurtosis15.46756889
Mean358977.7778
Median Absolute Deviation (MAD)20346.5
Skewness-3.56379116
Sum25846400
Variance2956434888
MonotonicityNot monotonic
2022-09-05T21:48:11.922220image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3602226
 
5.2%
3387385
 
4.3%
3699673
 
2.6%
3447502
 
1.7%
3226732
 
1.7%
3871532
 
1.7%
3926792
 
1.7%
3924102
 
1.7%
3932292
 
1.7%
3938702
 
1.7%
Other values (40)44
38.3%
(Missing)43
37.4%
ValueCountFrequency (%)
784191
0.9%
1042711
0.9%
2651931
0.9%
2724681
0.9%
2906861
0.9%
3196071
0.9%
3226732
1.7%
3287111
0.9%
3310952
1.7%
3386311
0.9%
ValueCountFrequency (%)
3940902
1.7%
3940871
0.9%
3940722
1.7%
3940451
0.9%
3938702
1.7%
3937431
0.9%
3935302
1.7%
3933371
0.9%
3932292
1.7%
3926792
1.7%

_embedded.show.externals.imdb
Categorical

HIGH CORRELATION
MISSING

Distinct34
Distinct (%)58.6%
Missing57
Missing (%)49.6%
Memory size1.0 KiB
tt11939550
tt12602588
tt8146760
tt10265028
 
3
tt11042298
 
2
Other values (29)
36 

Length

Max length10
Median length10
Mean length9.655172414
Min length9

Characters and Unicode

Total characters560
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)37.9%

Sample

1st rowtt8561620
2nd rowtt11477416
3rd rowtt11939550
4th rowtt11939550
5th rowtt11939550

Common Values

ValueCountFrequency (%)
tt119395506
 
5.2%
tt126025886
 
5.2%
tt81467605
 
4.3%
tt102650283
 
2.6%
tt110422982
 
1.7%
tt65948822
 
1.7%
tt125316622
 
1.7%
tt135688762
 
1.7%
tt135990002
 
1.7%
tt134703702
 
1.7%
Other values (24)26
22.6%
(Missing)57
49.6%

Length

2022-09-05T21:48:12.053403image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tt119395506
 
10.3%
tt126025886
 
10.3%
tt81467605
 
8.6%
tt102650283
 
5.2%
tt135990002
 
3.4%
tt136525522
 
3.4%
tt134703702
 
3.4%
tt88711282
 
3.4%
tt135688762
 
3.4%
tt125316622
 
3.4%
Other values (24)26
44.8%

Most occurring characters

ValueCountFrequency (%)
t116
20.7%
175
13.4%
655
9.8%
051
9.1%
851
9.1%
248
8.6%
546
 
8.2%
334
 
6.1%
430
 
5.4%
929
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number444
79.3%
Lowercase Letter116
 
20.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
175
16.9%
655
12.4%
051
11.5%
851
11.5%
248
10.8%
546
10.4%
334
7.7%
430
 
6.8%
929
 
6.5%
725
 
5.6%
Lowercase Letter
ValueCountFrequency (%)
t116
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common444
79.3%
Latin116
 
20.7%

Most frequent character per script

Common
ValueCountFrequency (%)
175
16.9%
655
12.4%
051
11.5%
851
11.5%
248
10.8%
546
10.4%
334
7.7%
430
 
6.8%
929
 
6.5%
725
 
5.6%
Latin
ValueCountFrequency (%)
t116
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII560
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t116
20.7%
175
13.4%
655
9.8%
051
9.1%
851
9.1%
248
8.6%
546
 
8.2%
334
 
6.1%
430
 
5.4%
929
 
5.2%

_embedded.show.image.medium
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct68
Distinct (%)62.4%
Missing6
Missing (%)5.2%
Memory size1.0 KiB
https://static.tvmaze.com/uploads/images/medium_portrait/290/726390.jpg
https://static.tvmaze.com/uploads/images/medium_portrait/290/726421.jpg
 
6
https://static.tvmaze.com/uploads/images/medium_portrait/189/473411.jpg
 
6
https://static.tvmaze.com/uploads/images/medium_portrait/291/729467.jpg
 
6
https://static.tvmaze.com/uploads/images/medium_portrait/382/956804.jpg
 
5
Other values (63)
78 

Length

Max length72
Median length71
Mean length71.03669725
Min length71

Characters and Unicode

Total characters7743
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)45.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_portrait/289/722910.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/260/651809.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/257/643435.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/257/643435.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/295/739859.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/290/726390.jpg8
 
7.0%
https://static.tvmaze.com/uploads/images/medium_portrait/290/726421.jpg6
 
5.2%
https://static.tvmaze.com/uploads/images/medium_portrait/189/473411.jpg6
 
5.2%
https://static.tvmaze.com/uploads/images/medium_portrait/291/729467.jpg6
 
5.2%
https://static.tvmaze.com/uploads/images/medium_portrait/382/956804.jpg5
 
4.3%
https://static.tvmaze.com/uploads/images/medium_portrait/295/739041.jpg3
 
2.6%
https://static.tvmaze.com/uploads/images/medium_portrait/291/729147.jpg2
 
1.7%
https://static.tvmaze.com/uploads/images/medium_portrait/291/729820.jpg2
 
1.7%
https://static.tvmaze.com/uploads/images/medium_portrait/398/996515.jpg2
 
1.7%
https://static.tvmaze.com/uploads/images/medium_portrait/269/673130.jpg2
 
1.7%
Other values (58)67
58.3%
(Missing)6
 
5.2%

Length

2022-09-05T21:48:12.159904image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/290/726390.jpg8
 
7.3%
https://static.tvmaze.com/uploads/images/medium_portrait/189/473411.jpg6
 
5.5%
https://static.tvmaze.com/uploads/images/medium_portrait/291/729467.jpg6
 
5.5%
https://static.tvmaze.com/uploads/images/medium_portrait/290/726421.jpg6
 
5.5%
https://static.tvmaze.com/uploads/images/medium_portrait/382/956804.jpg5
 
4.6%
https://static.tvmaze.com/uploads/images/medium_portrait/295/739041.jpg3
 
2.8%
https://static.tvmaze.com/uploads/images/medium_portrait/291/729740.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/394/986714.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/287/718741.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/298/745480.jpg2
 
1.8%
Other values (58)67
61.5%

Most occurring characters

ValueCountFrequency (%)
t763
 
9.9%
/763
 
9.9%
m545
 
7.0%
a545
 
7.0%
p436
 
5.6%
s436
 
5.6%
i436
 
5.6%
o327
 
4.2%
.327
 
4.2%
e327
 
4.2%
Other values (22)2838
36.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5450
70.4%
Other Punctuation1199
 
15.5%
Decimal Number985
 
12.7%
Connector Punctuation109
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t763
14.0%
m545
10.0%
a545
10.0%
p436
 
8.0%
s436
 
8.0%
i436
 
8.0%
o327
 
6.0%
e327
 
6.0%
u218
 
4.0%
c218
 
4.0%
Other values (8)1199
22.0%
Decimal Number
ValueCountFrequency (%)
2159
16.1%
9133
13.5%
7116
11.8%
1105
10.7%
496
9.7%
885
8.6%
380
8.1%
079
8.0%
674
7.5%
558
 
5.9%
Other Punctuation
ValueCountFrequency (%)
/763
63.6%
.327
27.3%
:109
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_109
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5450
70.4%
Common2293
29.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t763
14.0%
m545
10.0%
a545
10.0%
p436
 
8.0%
s436
 
8.0%
i436
 
8.0%
o327
 
6.0%
e327
 
6.0%
u218
 
4.0%
c218
 
4.0%
Other values (8)1199
22.0%
Common
ValueCountFrequency (%)
/763
33.3%
.327
14.3%
2159
 
6.9%
9133
 
5.8%
7116
 
5.1%
_109
 
4.8%
:109
 
4.8%
1105
 
4.6%
496
 
4.2%
885
 
3.7%
Other values (4)291
 
12.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII7743
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t763
 
9.9%
/763
 
9.9%
m545
 
7.0%
a545
 
7.0%
p436
 
5.6%
s436
 
5.6%
i436
 
5.6%
o327
 
4.2%
.327
 
4.2%
e327
 
4.2%
Other values (22)2838
36.7%

_embedded.show.image.original
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct68
Distinct (%)62.4%
Missing6
Missing (%)5.2%
Memory size1.0 KiB
https://static.tvmaze.com/uploads/images/original_untouched/290/726390.jpg
https://static.tvmaze.com/uploads/images/original_untouched/290/726421.jpg
 
6
https://static.tvmaze.com/uploads/images/original_untouched/189/473411.jpg
 
6
https://static.tvmaze.com/uploads/images/original_untouched/291/729467.jpg
 
6
https://static.tvmaze.com/uploads/images/original_untouched/382/956804.jpg
 
5
Other values (63)
78 

Length

Max length75
Median length74
Mean length74.03669725
Min length74

Characters and Unicode

Total characters8070
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)45.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/289/722910.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/260/651809.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/257/643435.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/257/643435.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/295/739859.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/290/726390.jpg8
 
7.0%
https://static.tvmaze.com/uploads/images/original_untouched/290/726421.jpg6
 
5.2%
https://static.tvmaze.com/uploads/images/original_untouched/189/473411.jpg6
 
5.2%
https://static.tvmaze.com/uploads/images/original_untouched/291/729467.jpg6
 
5.2%
https://static.tvmaze.com/uploads/images/original_untouched/382/956804.jpg5
 
4.3%
https://static.tvmaze.com/uploads/images/original_untouched/295/739041.jpg3
 
2.6%
https://static.tvmaze.com/uploads/images/original_untouched/291/729147.jpg2
 
1.7%
https://static.tvmaze.com/uploads/images/original_untouched/291/729820.jpg2
 
1.7%
https://static.tvmaze.com/uploads/images/original_untouched/398/996515.jpg2
 
1.7%
https://static.tvmaze.com/uploads/images/original_untouched/269/673130.jpg2
 
1.7%
Other values (58)67
58.3%
(Missing)6
 
5.2%

Length

2022-09-05T21:48:12.283046image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/290/726390.jpg8
 
7.3%
https://static.tvmaze.com/uploads/images/original_untouched/189/473411.jpg6
 
5.5%
https://static.tvmaze.com/uploads/images/original_untouched/291/729467.jpg6
 
5.5%
https://static.tvmaze.com/uploads/images/original_untouched/290/726421.jpg6
 
5.5%
https://static.tvmaze.com/uploads/images/original_untouched/382/956804.jpg5
 
4.6%
https://static.tvmaze.com/uploads/images/original_untouched/295/739041.jpg3
 
2.8%
https://static.tvmaze.com/uploads/images/original_untouched/291/729740.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/394/986714.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/287/718741.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/298/745480.jpg2
 
1.8%
Other values (58)67
61.5%

Most occurring characters

ValueCountFrequency (%)
/763
 
9.5%
t654
 
8.1%
a545
 
6.8%
s436
 
5.4%
i436
 
5.4%
o436
 
5.4%
p327
 
4.1%
c327
 
4.1%
.327
 
4.1%
g327
 
4.1%
Other values (23)3492
43.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5777
71.6%
Other Punctuation1199
 
14.9%
Decimal Number985
 
12.2%
Connector Punctuation109
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t654
 
11.3%
a545
 
9.4%
s436
 
7.5%
i436
 
7.5%
o436
 
7.5%
p327
 
5.7%
c327
 
5.7%
g327
 
5.7%
m327
 
5.7%
e327
 
5.7%
Other values (9)1635
28.3%
Decimal Number
ValueCountFrequency (%)
2159
16.1%
9133
13.5%
7116
11.8%
1105
10.7%
496
9.7%
885
8.6%
380
8.1%
079
8.0%
674
7.5%
558
 
5.9%
Other Punctuation
ValueCountFrequency (%)
/763
63.6%
.327
27.3%
:109
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_109
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5777
71.6%
Common2293
 
28.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t654
 
11.3%
a545
 
9.4%
s436
 
7.5%
i436
 
7.5%
o436
 
7.5%
p327
 
5.7%
c327
 
5.7%
g327
 
5.7%
m327
 
5.7%
e327
 
5.7%
Other values (9)1635
28.3%
Common
ValueCountFrequency (%)
/763
33.3%
.327
14.3%
2159
 
6.9%
9133
 
5.8%
7116
 
5.1%
:109
 
4.8%
_109
 
4.8%
1105
 
4.6%
496
 
4.2%
885
 
3.7%
Other values (4)291
 
12.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII8070
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/763
 
9.5%
t654
 
8.1%
a545
 
6.8%
s436
 
5.4%
i436
 
5.4%
o436
 
5.4%
p327
 
4.1%
c327
 
4.1%
.327
 
4.1%
g327
 
4.1%
Other values (23)3492
43.3%

_embedded.show.summary
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct65
Distinct (%)61.9%
Missing10
Missing (%)8.7%
Memory size1.0 KiB
<p>Anuradha Chandra stabs her perfect lawyer husband one fateful night and confesses to her crime. However, it is anything but an open-and-shut case.</p>
<p>Lin Luo Jing accidentally gets drawn into a game world where she is the daughter of the prime minister and meets all kind of beautiful men with different personalities. Among them are a sword deity, an imperial bodyguard, a playful rich man and an arrogant prince. The system informs her that she can only return to the real world after she finds her true love. While there seems tobe an abundance of good men around Luo Jing, there is one man she can't stand at all: the prince of the barbarian Yuan Kingdom Zhong Wu Mei. But out of all men, she ends up in an arranged marriage with Wu Mei.</p><p>Thus begins their love-hate relationship and her journey to find true love in order to win the game.</p>
 
6
<p><b>Feluda Pherot</b> is the return of the iconic Feluda, Asia's Brightest Crime Detector, along with his comrades Jatayu and Topshe, unraveling more mysteries.</p>
 
6
<p>Lin Luojing enters the XR system due to a technology competition, and time-travels to the Sheng Yuan Dynasty of the game. To return back to reality, she has to find her true love and max the "favorability points". In the midst of exchanging tactics with arrogant prince Zhong Wu Mei, her former personal guard Liu Xiu Wen returns to the capital, this time with a new identity as the Persian Prince. Liu Xiu Wen vows to wage war on Zhong Wuyan. Facing both internal and external crises and conflicts, how will Lin Luojing resolve it and embark on her journey back home?</p>
 
6
<p>Set in a world of anthropomorphic animals, Summer Camp Island follows two best friends Oscar, and Hedgehog, and Oscar who are dropped off at a surreal summer camp. The camp is a host to many odd occurrences such as: camp counselors who are composed of popular girls who know magic, horses that transform into unicorns, talking sharks, post-it notes that lead to other dimensions and nosy monsters that live under the bed. Oscar and Hedgehog must contend with these out of place events and make their stay at camp worthwhile.</p>
 
5
Other values (60)
74 

Length

Max length1483
Median length547
Mean length396.1047619
Min length90

Characters and Unicode

Total characters41591
Distinct characters92
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)44.8%

Sample

1st row<p>Marina is in her late 30s, she has a successful business and a close-knit family. Her husband is a surgeon and her daughters study at fancy establishments. To everybody her life seems perfect. Though, it is all just a facade concealing the real problems: her husband has a mistress, her elder daughter is a slacker and drug-dealer, her youngest is a sociopath. Well, Marina herself is not really a flower-lady, but a brothel-keeper who is hiding her dark business from everyone. The truth may come out when a girl of Marina's is found dead.</p>
2nd row<p>When terminal cancer patient Zhenya unexpectedly receives a clean bill of health, she can't believe it. She's in remission. But then her life implodes. Homeless, unemployed, and newly single - she stumbles across a list she wrote while she was sick of things she wanted to do when she got better. 257 of them - and now she won't give up until she checks off them all!</p>
3rd row<p>Stories about friendship and adventures of charming round heroes. Fun and musical, unexpected and dreamy, homely and adventurous. The whole world in one cozy chamomile valley.</p>
4th row<p>Stories about friendship and adventures of charming round heroes. Fun and musical, unexpected and dreamy, homely and adventurous. The whole world in one cozy chamomile valley.</p>
5th row<p>Oleg is a metropolitan psychotherapist. Clients of the central district of Moscow line up to him. Only lately Oleg doesn't like them, he tolerates them. Midlife crisis, life with mom at 40, loss of self-esteem, drug addiction, irritability and growing aggression. None of the clients are aware of his problems. From the outside, he seems successful, happily married, wealthy. Nobody knows the truth.</p><p> </p><p>A year ago, his wife went missing. She has been gone for 384 days.</p>

Common Values

ValueCountFrequency (%)
<p>Anuradha Chandra stabs her perfect lawyer husband one fateful night and confesses to her crime. However, it is anything but an open-and-shut case.</p>8
 
7.0%
<p>Lin Luo Jing accidentally gets drawn into a game world where she is the daughter of the prime minister and meets all kind of beautiful men with different personalities. Among them are a sword deity, an imperial bodyguard, a playful rich man and an arrogant prince. The system informs her that she can only return to the real world after she finds her true love. While there seems tobe an abundance of good men around Luo Jing, there is one man she can't stand at all: the prince of the barbarian Yuan Kingdom Zhong Wu Mei. But out of all men, she ends up in an arranged marriage with Wu Mei.</p><p>Thus begins their love-hate relationship and her journey to find true love in order to win the game.</p>6
 
5.2%
<p><b>Feluda Pherot</b> is the return of the iconic Feluda, Asia's Brightest Crime Detector, along with his comrades Jatayu and Topshe, unraveling more mysteries.</p>6
 
5.2%
<p>Lin Luojing enters the XR system due to a technology competition, and time-travels to the Sheng Yuan Dynasty of the game. To return back to reality, she has to find her true love and max the "favorability points". In the midst of exchanging tactics with arrogant prince Zhong Wu Mei, her former personal guard Liu Xiu Wen returns to the capital, this time with a new identity as the Persian Prince. Liu Xiu Wen vows to wage war on Zhong Wuyan. Facing both internal and external crises and conflicts, how will Lin Luojing resolve it and embark on her journey back home?</p>6
 
5.2%
<p>Set in a world of anthropomorphic animals, Summer Camp Island follows two best friends Oscar, and Hedgehog, and Oscar who are dropped off at a surreal summer camp. The camp is a host to many odd occurrences such as: camp counselors who are composed of popular girls who know magic, horses that transform into unicorns, talking sharks, post-it notes that lead to other dimensions and nosy monsters that live under the bed. Oscar and Hedgehog must contend with these out of place events and make their stay at camp worthwhile.</p>5
 
4.3%
<p><b>Off the Cuff </b>explores the world's most unique, exciting, and often misrepresented communities.</p>3
 
2.6%
<p>Yoon Bo Mi of Apink Comedian Kim Min Kyoung, the former rhythmic gymnast Shin Soo Ji, Cheerleader Park Ki Ryang, Anchorwoman Park Ji Young, and Actress Kang So Yeon are huge fans of baseball. They come together to actually try playing baseball themselves instead of just watching it. Although they all work in different industries, they unite thanks to their mutual love of the sport. Together, they strive to compete against other amateur teams. Will their earnest desire to work together and their ambition to win make all the difference? How will they grow together as a team?</p>2
 
1.7%
<p>Curious about his uncle's past, Wu Xie watched a mysterious videotape, only to find himself mixed up in an elaborate conspiracy. In his adventures, he encountered Zhang Qi Ling, Xie Yu Chen, and others. </p>2
 
1.7%
<p>Harun and Hande are brothers with opposite characters. Hande is a professional business woman in the tourism industry.</p>2
 
1.7%
<p>Stories about friendship and adventures of charming round heroes. Fun and musical, unexpected and dreamy, homely and adventurous. The whole world in one cozy chamomile valley.</p>2
 
1.7%
Other values (55)63
54.8%
(Missing)10
 
8.7%

Length

2022-09-05T21:48:12.449450image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the367
 
5.2%
and270
 
3.9%
of200
 
2.9%
a195
 
2.8%
to193
 
2.8%
in113
 
1.6%
her93
 
1.3%
is89
 
1.3%
with81
 
1.2%
she59
 
0.8%
Other values (1733)5346
76.3%

Most occurring characters

ValueCountFrequency (%)
6892
16.6%
e3822
 
9.2%
a2700
 
6.5%
t2568
 
6.2%
n2527
 
6.1%
o2331
 
5.6%
i2269
 
5.5%
s2082
 
5.0%
r2037
 
4.9%
h1765
 
4.2%
Other values (82)12598
30.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter31504
75.7%
Space Separator6902
 
16.6%
Uppercase Letter1311
 
3.2%
Other Punctuation1102
 
2.6%
Math Symbol624
 
1.5%
Dash Punctuation76
 
0.2%
Decimal Number47
 
0.1%
Format12
 
< 0.1%
Open Punctuation6
 
< 0.1%
Close Punctuation6
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e3822
12.1%
a2700
 
8.6%
t2568
 
8.2%
n2527
 
8.0%
o2331
 
7.4%
i2269
 
7.2%
s2082
 
6.6%
r2037
 
6.5%
h1765
 
5.6%
l1244
 
3.9%
Other values (23)8159
25.9%
Uppercase Letter
ValueCountFrequency (%)
T145
 
11.1%
S110
 
8.4%
W93
 
7.1%
A83
 
6.3%
L82
 
6.3%
X70
 
5.3%
M62
 
4.7%
C61
 
4.7%
B54
 
4.1%
Y53
 
4.0%
Other values (16)498
38.0%
Other Punctuation
ValueCountFrequency (%)
,429
38.9%
.332
30.1%
/162
 
14.7%
'77
 
7.0%
"40
 
3.6%
:21
 
1.9%
?17
 
1.5%
!13
 
1.2%
;7
 
0.6%
&1
 
0.1%
Other values (3)3
 
0.3%
Decimal Number
ValueCountFrequency (%)
014
29.8%
26
12.8%
16
12.8%
55
 
10.6%
44
 
8.5%
63
 
6.4%
33
 
6.4%
72
 
4.3%
82
 
4.3%
92
 
4.3%
Space Separator
ValueCountFrequency (%)
6892
99.9%
 10
 
0.1%
Math Symbol
ValueCountFrequency (%)
<312
50.0%
>312
50.0%
Dash Punctuation
ValueCountFrequency (%)
-67
88.2%
9
 
11.8%
Format
ValueCountFrequency (%)
12
100.0%
Open Punctuation
ValueCountFrequency (%)
(6
100.0%
Close Punctuation
ValueCountFrequency (%)
)6
100.0%
Currency Symbol
ValueCountFrequency (%)
$1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin32815
78.9%
Common8776
 
21.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e3822
11.6%
a2700
 
8.2%
t2568
 
7.8%
n2527
 
7.7%
o2331
 
7.1%
i2269
 
6.9%
s2082
 
6.3%
r2037
 
6.2%
h1765
 
5.4%
l1244
 
3.8%
Other values (49)9470
28.9%
Common
ValueCountFrequency (%)
6892
78.5%
,429
 
4.9%
.332
 
3.8%
<312
 
3.6%
>312
 
3.6%
/162
 
1.8%
'77
 
0.9%
-67
 
0.8%
"40
 
0.5%
:21
 
0.2%
Other values (23)132
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII41551
99.9%
Punctuation22
 
0.1%
None18
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6892
16.6%
e3822
 
9.2%
a2700
 
6.5%
t2568
 
6.2%
n2527
 
6.1%
o2331
 
5.6%
i2269
 
5.5%
s2082
 
5.0%
r2037
 
4.9%
h1765
 
4.2%
Other values (71)12558
30.2%
Punctuation
ValueCountFrequency (%)
12
54.5%
9
40.9%
1
 
4.5%
None
ValueCountFrequency (%)
 10
55.6%
č2
 
11.1%
ö1
 
5.6%
ū1
 
5.6%
ã1
 
5.6%
ê1
 
5.6%
ė1
 
5.6%
å1
 
5.6%

_embedded.show.updated
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct73
Distinct (%)63.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1640871901
Minimum1608845017
Maximum1662346277
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-05T21:48:12.612084image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1608845017
5-th percentile1608845017
Q11625582310
median1646488908
Q31656989414
95-th percentile1661649600
Maximum1662346277
Range53501260
Interquartile range (IQR)31407104.5

Descriptive statistics

Standard deviation19112869.77
Coefficient of variation (CV)0.01164799626
Kurtosis-1.039608573
Mean1640871901
Median Absolute Deviation (MAD)13054197
Skewness-0.6660747708
Sum1.887002686 × 1011
Variance3.653017907 × 1014
MonotonicityNot monotonic
2022-09-05T21:48:12.761199image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16088450178
 
7.0%
16088492216
 
5.2%
16602618866
 
5.2%
16543820716
 
5.2%
16393002025
 
4.3%
16410489583
 
2.6%
16407890402
 
1.7%
16400183662
 
1.7%
16357351792
 
1.7%
16491780842
 
1.7%
Other values (63)73
63.5%
ValueCountFrequency (%)
16088450178
7.0%
16088492216
5.2%
16096167881
 
0.9%
16097847492
 
1.7%
16101108411
 
0.9%
16109073001
 
0.9%
16114368421
 
0.9%
16119369521
 
0.9%
16125166641
 
0.9%
16131487841
 
0.9%
ValueCountFrequency (%)
16623462771
0.9%
16622800111
0.9%
16618640442
1.7%
16617704651
0.9%
16616900451
0.9%
16616322671
0.9%
16615261291
0.9%
16614348681
0.9%
16613636441
0.9%
16612645191
0.9%

_embedded.show._links.self.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct73
Distinct (%)63.5%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
https://api.tvmaze.com/shows/52609
 
8
https://api.tvmaze.com/shows/52610
 
6
https://api.tvmaze.com/shows/52784
 
6
https://api.tvmaze.com/shows/41490
 
6
https://api.tvmaze.com/shows/26643
 
5
Other values (68)
84 

Length

Max length34
Median length34
Mean length33.97391304
Min length33

Characters and Unicode

Total characters3907
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)46.1%

Sample

1st rowhttps://api.tvmaze.com/shows/39115
2nd rowhttps://api.tvmaze.com/shows/43722
3rd rowhttps://api.tvmaze.com/shows/48151
4th rowhttps://api.tvmaze.com/shows/48151
5th rowhttps://api.tvmaze.com/shows/49280

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/shows/526098
 
7.0%
https://api.tvmaze.com/shows/526106
 
5.2%
https://api.tvmaze.com/shows/527846
 
5.2%
https://api.tvmaze.com/shows/414906
 
5.2%
https://api.tvmaze.com/shows/266435
 
4.3%
https://api.tvmaze.com/shows/533193
 
2.6%
https://api.tvmaze.com/shows/498432
 
1.7%
https://api.tvmaze.com/shows/551992
 
1.7%
https://api.tvmaze.com/shows/586892
 
1.7%
https://api.tvmaze.com/shows/528062
 
1.7%
Other values (63)73
63.5%

Length

2022-09-05T21:48:12.878532image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/shows/526098
 
7.0%
https://api.tvmaze.com/shows/527846
 
5.2%
https://api.tvmaze.com/shows/414906
 
5.2%
https://api.tvmaze.com/shows/526106
 
5.2%
https://api.tvmaze.com/shows/266435
 
4.3%
https://api.tvmaze.com/shows/533193
 
2.6%
https://api.tvmaze.com/shows/524212
 
1.7%
https://api.tvmaze.com/shows/608482
 
1.7%
https://api.tvmaze.com/shows/479122
 
1.7%
https://api.tvmaze.com/shows/538302
 
1.7%
Other values (63)73
63.5%

Most occurring characters

ValueCountFrequency (%)
/460
 
11.8%
s345
 
8.8%
t345
 
8.8%
h230
 
5.9%
p230
 
5.9%
a230
 
5.9%
o230
 
5.9%
.230
 
5.9%
m230
 
5.9%
e115
 
2.9%
Other values (16)1262
32.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2530
64.8%
Other Punctuation805
 
20.6%
Decimal Number572
 
14.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s345
13.6%
t345
13.6%
h230
9.1%
p230
9.1%
a230
9.1%
o230
9.1%
m230
9.1%
e115
 
4.5%
w115
 
4.5%
c115
 
4.5%
Other values (3)345
13.6%
Decimal Number
ValueCountFrequency (%)
591
15.9%
470
12.2%
266
11.5%
662
10.8%
958
10.1%
054
9.4%
152
9.1%
849
8.6%
342
7.3%
728
 
4.9%
Other Punctuation
ValueCountFrequency (%)
/460
57.1%
.230
28.6%
:115
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2530
64.8%
Common1377
35.2%

Most frequent character per script

Common
ValueCountFrequency (%)
/460
33.4%
.230
16.7%
:115
 
8.4%
591
 
6.6%
470
 
5.1%
266
 
4.8%
662
 
4.5%
958
 
4.2%
054
 
3.9%
152
 
3.8%
Other values (3)119
 
8.6%
Latin
ValueCountFrequency (%)
s345
13.6%
t345
13.6%
h230
9.1%
p230
9.1%
a230
9.1%
o230
9.1%
m230
9.1%
e115
 
4.5%
w115
 
4.5%
c115
 
4.5%
Other values (3)345
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII3907
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/460
 
11.8%
s345
 
8.8%
t345
 
8.8%
h230
 
5.9%
p230
 
5.9%
a230
 
5.9%
o230
 
5.9%
.230
 
5.9%
m230
 
5.9%
e115
 
2.9%
Other values (16)1262
32.3%

_embedded.show._links.previousepisode.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct73
Distinct (%)63.5%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
https://api.tvmaze.com/episodes/1991045
 
8
https://api.tvmaze.com/episodes/1991212
 
6
https://api.tvmaze.com/episodes/1998626
 
6
https://api.tvmaze.com/episodes/2324440
 
6
https://api.tvmaze.com/episodes/2234373
 
5
Other values (68)
84 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters4485
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)46.1%

Sample

1st rowhttps://api.tvmaze.com/episodes/1977905
2nd rowhttps://api.tvmaze.com/episodes/1964003
3rd rowhttps://api.tvmaze.com/episodes/2164183
4th rowhttps://api.tvmaze.com/episodes/2164183
5th rowhttps://api.tvmaze.com/episodes/1960733

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19910458
 
7.0%
https://api.tvmaze.com/episodes/19912126
 
5.2%
https://api.tvmaze.com/episodes/19986266
 
5.2%
https://api.tvmaze.com/episodes/23244406
 
5.2%
https://api.tvmaze.com/episodes/22343735
 
4.3%
https://api.tvmaze.com/episodes/20294553
 
2.6%
https://api.tvmaze.com/episodes/22400412
 
1.7%
https://api.tvmaze.com/episodes/20876122
 
1.7%
https://api.tvmaze.com/episodes/22059832
 
1.7%
https://api.tvmaze.com/episodes/20000832
 
1.7%
Other values (63)73
63.5%

Length

2022-09-05T21:48:12.967875image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19910458
 
7.0%
https://api.tvmaze.com/episodes/19986266
 
5.2%
https://api.tvmaze.com/episodes/23244406
 
5.2%
https://api.tvmaze.com/episodes/19912126
 
5.2%
https://api.tvmaze.com/episodes/22343735
 
4.3%
https://api.tvmaze.com/episodes/20294553
 
2.6%
https://api.tvmaze.com/episodes/19854962
 
1.7%
https://api.tvmaze.com/episodes/22894182
 
1.7%
https://api.tvmaze.com/episodes/19725912
 
1.7%
https://api.tvmaze.com/episodes/20396272
 
1.7%
Other values (63)73
63.5%

Most occurring characters

ValueCountFrequency (%)
/460
 
10.3%
t345
 
7.7%
p345
 
7.7%
s345
 
7.7%
e345
 
7.7%
a230
 
5.1%
i230
 
5.1%
.230
 
5.1%
m230
 
5.1%
o230
 
5.1%
Other values (16)1495
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2875
64.1%
Other Punctuation805
 
17.9%
Decimal Number805
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t345
12.0%
p345
12.0%
s345
12.0%
e345
12.0%
a230
8.0%
i230
8.0%
m230
8.0%
o230
8.0%
h115
 
4.0%
d115
 
4.0%
Other values (3)345
12.0%
Decimal Number
ValueCountFrequency (%)
2162
20.1%
9106
13.2%
1104
12.9%
380
9.9%
076
9.4%
470
8.7%
556
 
7.0%
754
 
6.7%
650
 
6.2%
847
 
5.8%
Other Punctuation
ValueCountFrequency (%)
/460
57.1%
.230
28.6%
:115
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2875
64.1%
Common1610
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/460
28.6%
.230
14.3%
2162
 
10.1%
:115
 
7.1%
9106
 
6.6%
1104
 
6.5%
380
 
5.0%
076
 
4.7%
470
 
4.3%
556
 
3.5%
Other values (3)151
 
9.4%
Latin
ValueCountFrequency (%)
t345
12.0%
p345
12.0%
s345
12.0%
e345
12.0%
a230
8.0%
i230
8.0%
m230
8.0%
o230
8.0%
h115
 
4.0%
d115
 
4.0%
Other values (3)345
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII4485
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/460
 
10.3%
t345
 
7.7%
p345
 
7.7%
s345
 
7.7%
e345
 
7.7%
a230
 
5.1%
i230
 
5.1%
.230
 
5.1%
m230
 
5.1%
o230
 
5.1%
Other values (16)1495
33.3%

image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing115
Missing (%)100.0%
Memory size1.0 KiB

_embedded.show.webChannel.country
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing115
Missing (%)100.0%
Memory size1.0 KiB

_embedded.show._links.nextepisode.href
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct5
Distinct (%)100.0%
Missing110
Missing (%)95.7%
Memory size1.0 KiB
https://api.tvmaze.com/episodes/2381297
https://api.tvmaze.com/episodes/2371615
https://api.tvmaze.com/episodes/2370312
https://api.tvmaze.com/episodes/2379703
https://api.tvmaze.com/episodes/2382043

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters195
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2381297
2nd rowhttps://api.tvmaze.com/episodes/2371615
3rd rowhttps://api.tvmaze.com/episodes/2370312
4th rowhttps://api.tvmaze.com/episodes/2379703
5th rowhttps://api.tvmaze.com/episodes/2382043

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/23812971
 
0.9%
https://api.tvmaze.com/episodes/23716151
 
0.9%
https://api.tvmaze.com/episodes/23703121
 
0.9%
https://api.tvmaze.com/episodes/23797031
 
0.9%
https://api.tvmaze.com/episodes/23820431
 
0.9%
(Missing)110
95.7%

Length

2022-09-05T21:48:13.062015image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:48:13.161775image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/23812971
20.0%
https://api.tvmaze.com/episodes/23716151
20.0%
https://api.tvmaze.com/episodes/23703121
20.0%
https://api.tvmaze.com/episodes/23797031
20.0%
https://api.tvmaze.com/episodes/23820431
20.0%

Most occurring characters

ValueCountFrequency (%)
/20
 
10.3%
p15
 
7.7%
s15
 
7.7%
e15
 
7.7%
t15
 
7.7%
a10
 
5.1%
i10
 
5.1%
.10
 
5.1%
m10
 
5.1%
o10
 
5.1%
Other values (16)65
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter125
64.1%
Other Punctuation35
 
17.9%
Decimal Number35
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p15
12.0%
s15
12.0%
e15
12.0%
t15
12.0%
a10
8.0%
i10
8.0%
m10
8.0%
o10
8.0%
h5
 
4.0%
d5
 
4.0%
Other values (3)15
12.0%
Decimal Number
ValueCountFrequency (%)
38
22.9%
28
22.9%
75
14.3%
14
11.4%
03
 
8.6%
82
 
5.7%
92
 
5.7%
61
 
2.9%
51
 
2.9%
41
 
2.9%
Other Punctuation
ValueCountFrequency (%)
/20
57.1%
.10
28.6%
:5
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin125
64.1%
Common70
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/20
28.6%
.10
14.3%
38
 
11.4%
28
 
11.4%
75
 
7.1%
:5
 
7.1%
14
 
5.7%
03
 
4.3%
82
 
2.9%
92
 
2.9%
Other values (3)3
 
4.3%
Latin
ValueCountFrequency (%)
p15
12.0%
s15
12.0%
e15
12.0%
t15
12.0%
a10
8.0%
i10
8.0%
m10
8.0%
o10
8.0%
h5
 
4.0%
d5
 
4.0%
Other values (3)15
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII195
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/20
 
10.3%
p15
 
7.7%
s15
 
7.7%
e15
 
7.7%
t15
 
7.7%
a10
 
5.1%
i10
 
5.1%
.10
 
5.1%
m10
 
5.1%
o10
 
5.1%
Other values (16)65
33.3%

_embedded.show.image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing115
Missing (%)100.0%
Memory size1.0 KiB

_embedded.show.network.id
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct4
Distinct (%)100.0%
Missing111
Missing (%)96.5%
Memory size1.0 KiB
1766.0
1808.0
127.0
112.0

Length

Max length6
Median length5.5
Mean length5.5
Min length5

Characters and Unicode

Total characters22
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st row1766.0
2nd row1808.0
3rd row127.0
4th row112.0

Common Values

ValueCountFrequency (%)
1766.01
 
0.9%
1808.01
 
0.9%
127.01
 
0.9%
112.01
 
0.9%
(Missing)111
96.5%

Length

2022-09-05T21:48:13.268129image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:48:13.380187image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
1766.01
25.0%
1808.01
25.0%
127.01
25.0%
112.01
25.0%

Most occurring characters

ValueCountFrequency (%)
15
22.7%
05
22.7%
.4
18.2%
72
 
9.1%
62
 
9.1%
82
 
9.1%
22
 
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number18
81.8%
Other Punctuation4
 
18.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
15
27.8%
05
27.8%
72
 
11.1%
62
 
11.1%
82
 
11.1%
22
 
11.1%
Other Punctuation
ValueCountFrequency (%)
.4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common22
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
15
22.7%
05
22.7%
.4
18.2%
72
 
9.1%
62
 
9.1%
82
 
9.1%
22
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII22
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15
22.7%
05
22.7%
.4
18.2%
72
 
9.1%
62
 
9.1%
82
 
9.1%
22
 
9.1%

_embedded.show.network.name
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct4
Distinct (%)100.0%
Missing111
Missing (%)96.5%
Memory size1.0 KiB
Alarby Television
MBC Masr
SBS
RTL4

Length

Max length17
Median length6
Mean length8
Min length3

Characters and Unicode

Total characters32
Distinct characters21
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st rowAlarby Television
2nd rowMBC Masr
3rd rowSBS
4th rowRTL4

Common Values

ValueCountFrequency (%)
Alarby Television1
 
0.9%
MBC Masr1
 
0.9%
SBS1
 
0.9%
RTL41
 
0.9%
(Missing)111
96.5%

Length

2022-09-05T21:48:13.480838image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:48:13.590212image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
alarby1
16.7%
television1
16.7%
mbc1
16.7%
masr1
16.7%
sbs1
16.7%
rtl41
16.7%

Most occurring characters

ValueCountFrequency (%)
i2
 
6.2%
M2
 
6.2%
a2
 
6.2%
r2
 
6.2%
2
 
6.2%
T2
 
6.2%
e2
 
6.2%
S2
 
6.2%
l2
 
6.2%
s2
 
6.2%
Other values (11)12
37.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter17
53.1%
Uppercase Letter12
37.5%
Space Separator2
 
6.2%
Decimal Number1
 
3.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i2
11.8%
a2
11.8%
r2
11.8%
e2
11.8%
l2
11.8%
s2
11.8%
n1
5.9%
o1
5.9%
v1
5.9%
y1
5.9%
Uppercase Letter
ValueCountFrequency (%)
M2
16.7%
T2
16.7%
S2
16.7%
B2
16.7%
L1
8.3%
R1
8.3%
C1
8.3%
A1
8.3%
Space Separator
ValueCountFrequency (%)
2
100.0%
Decimal Number
ValueCountFrequency (%)
41
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin29
90.6%
Common3
 
9.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
i2
 
6.9%
M2
 
6.9%
a2
 
6.9%
r2
 
6.9%
T2
 
6.9%
e2
 
6.9%
S2
 
6.9%
l2
 
6.9%
s2
 
6.9%
B2
 
6.9%
Other values (9)9
31.0%
Common
ValueCountFrequency (%)
2
66.7%
41
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII32
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i2
 
6.2%
M2
 
6.2%
a2
 
6.2%
r2
 
6.2%
2
 
6.2%
T2
 
6.2%
e2
 
6.2%
S2
 
6.2%
l2
 
6.2%
s2
 
6.2%
Other values (11)12
37.5%

_embedded.show.network.country.name
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct4
Distinct (%)100.0%
Missing111
Missing (%)96.5%
Memory size1.0 KiB
Saudi Arabia
Egypt
Korea, Republic of
Netherlands

Length

Max length18
Median length11.5
Mean length11.5
Min length5

Characters and Unicode

Total characters46
Distinct characters26
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st rowSaudi Arabia
2nd rowEgypt
3rd rowKorea, Republic of
4th rowNetherlands

Common Values

ValueCountFrequency (%)
Saudi Arabia1
 
0.9%
Egypt1
 
0.9%
Korea, Republic of1
 
0.9%
Netherlands1
 
0.9%
(Missing)111
96.5%

Length

2022-09-05T21:48:13.689981image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:48:13.797166image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
saudi1
14.3%
arabia1
14.3%
egypt1
14.3%
korea1
14.3%
republic1
14.3%
of1
14.3%
netherlands1
14.3%

Most occurring characters

ValueCountFrequency (%)
a5
 
10.9%
e4
 
8.7%
i3
 
6.5%
3
 
6.5%
r3
 
6.5%
t2
 
4.3%
p2
 
4.3%
o2
 
4.3%
l2
 
4.3%
b2
 
4.3%
Other values (16)18
39.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter36
78.3%
Uppercase Letter6
 
13.0%
Space Separator3
 
6.5%
Other Punctuation1
 
2.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a5
13.9%
e4
11.1%
i3
 
8.3%
r3
 
8.3%
t2
 
5.6%
p2
 
5.6%
o2
 
5.6%
l2
 
5.6%
b2
 
5.6%
d2
 
5.6%
Other values (8)9
25.0%
Uppercase Letter
ValueCountFrequency (%)
R1
16.7%
N1
16.7%
S1
16.7%
K1
16.7%
E1
16.7%
A1
16.7%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
,1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin42
91.3%
Common4
 
8.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a5
 
11.9%
e4
 
9.5%
i3
 
7.1%
r3
 
7.1%
t2
 
4.8%
p2
 
4.8%
o2
 
4.8%
l2
 
4.8%
b2
 
4.8%
d2
 
4.8%
Other values (14)15
35.7%
Common
ValueCountFrequency (%)
3
75.0%
,1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII46
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a5
 
10.9%
e4
 
8.7%
i3
 
6.5%
3
 
6.5%
r3
 
6.5%
t2
 
4.3%
p2
 
4.3%
o2
 
4.3%
l2
 
4.3%
b2
 
4.3%
Other values (16)18
39.1%

_embedded.show.network.country.code
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct4
Distinct (%)100.0%
Missing111
Missing (%)96.5%
Memory size1.0 KiB
SA
EG
KR
NL

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters8
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st rowSA
2nd rowEG
3rd rowKR
4th rowNL

Common Values

ValueCountFrequency (%)
SA1
 
0.9%
EG1
 
0.9%
KR1
 
0.9%
NL1
 
0.9%
(Missing)111
96.5%

Length

2022-09-05T21:48:13.892519image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:48:14.000079image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
sa1
25.0%
eg1
25.0%
kr1
25.0%
nl1
25.0%

Most occurring characters

ValueCountFrequency (%)
S1
12.5%
A1
12.5%
E1
12.5%
G1
12.5%
K1
12.5%
R1
12.5%
N1
12.5%
L1
12.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter8
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S1
12.5%
A1
12.5%
E1
12.5%
G1
12.5%
K1
12.5%
R1
12.5%
N1
12.5%
L1
12.5%

Most occurring scripts

ValueCountFrequency (%)
Latin8
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S1
12.5%
A1
12.5%
E1
12.5%
G1
12.5%
K1
12.5%
R1
12.5%
N1
12.5%
L1
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII8
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S1
12.5%
A1
12.5%
E1
12.5%
G1
12.5%
K1
12.5%
R1
12.5%
N1
12.5%
L1
12.5%

_embedded.show.network.country.timezone
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct4
Distinct (%)100.0%
Missing111
Missing (%)96.5%
Memory size1.0 KiB
Asia/Riyadh
Africa/Cairo
Asia/Seoul
Europe/Amsterdam

Length

Max length16
Median length11.5
Mean length12.25
Min length10

Characters and Unicode

Total characters49
Distinct characters22
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st rowAsia/Riyadh
2nd rowAfrica/Cairo
3rd rowAsia/Seoul
4th rowEurope/Amsterdam

Common Values

ValueCountFrequency (%)
Asia/Riyadh1
 
0.9%
Africa/Cairo1
 
0.9%
Asia/Seoul1
 
0.9%
Europe/Amsterdam1
 
0.9%
(Missing)111
96.5%

Length

2022-09-05T21:48:14.103144image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:48:14.214654image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
asia/riyadh1
25.0%
africa/cairo1
25.0%
asia/seoul1
25.0%
europe/amsterdam1
25.0%

Most occurring characters

ValueCountFrequency (%)
a6
12.2%
i5
 
10.2%
A4
 
8.2%
/4
 
8.2%
r4
 
8.2%
e3
 
6.1%
s3
 
6.1%
o3
 
6.1%
m2
 
4.1%
d2
 
4.1%
Other values (12)13
26.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter37
75.5%
Uppercase Letter8
 
16.3%
Other Punctuation4
 
8.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a6
16.2%
i5
13.5%
r4
10.8%
e3
8.1%
s3
8.1%
o3
8.1%
m2
 
5.4%
d2
 
5.4%
u2
 
5.4%
p1
 
2.7%
Other values (6)6
16.2%
Uppercase Letter
ValueCountFrequency (%)
A4
50.0%
E1
 
12.5%
S1
 
12.5%
C1
 
12.5%
R1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
/4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin45
91.8%
Common4
 
8.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a6
13.3%
i5
11.1%
A4
 
8.9%
r4
 
8.9%
e3
 
6.7%
s3
 
6.7%
o3
 
6.7%
m2
 
4.4%
d2
 
4.4%
u2
 
4.4%
Other values (11)11
24.4%
Common
ValueCountFrequency (%)
/4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII49
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a6
12.2%
i5
 
10.2%
A4
 
8.2%
/4
 
8.2%
r4
 
8.2%
e3
 
6.1%
s3
 
6.1%
o3
 
6.1%
m2
 
4.1%
d2
 
4.1%
Other values (12)13
26.5%

_embedded.show.network.officialSite
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing115
Missing (%)100.0%
Memory size1.0 KiB

_embedded.show.dvdCountry.name
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing114
Missing (%)99.1%
Memory size1.0 KiB
Korea, Republic of

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters18
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowKorea, Republic of

Common Values

ValueCountFrequency (%)
Korea, Republic of1
 
0.9%
(Missing)114
99.1%

Length

2022-09-05T21:48:14.304963image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:48:14.391195image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
korea1
33.3%
republic1
33.3%
of1
33.3%

Most occurring characters

ValueCountFrequency (%)
o2
 
11.1%
e2
 
11.1%
2
 
11.1%
K1
 
5.6%
r1
 
5.6%
a1
 
5.6%
,1
 
5.6%
R1
 
5.6%
p1
 
5.6%
u1
 
5.6%
Other values (5)5
27.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter13
72.2%
Space Separator2
 
11.1%
Uppercase Letter2
 
11.1%
Other Punctuation1
 
5.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o2
15.4%
e2
15.4%
r1
7.7%
a1
7.7%
p1
7.7%
u1
7.7%
b1
7.7%
l1
7.7%
i1
7.7%
c1
7.7%
Uppercase Letter
ValueCountFrequency (%)
K1
50.0%
R1
50.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Punctuation
ValueCountFrequency (%)
,1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin15
83.3%
Common3
 
16.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
o2
13.3%
e2
13.3%
K1
 
6.7%
r1
 
6.7%
a1
 
6.7%
R1
 
6.7%
p1
 
6.7%
u1
 
6.7%
b1
 
6.7%
l1
 
6.7%
Other values (3)3
20.0%
Common
ValueCountFrequency (%)
2
66.7%
,1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII18
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o2
 
11.1%
e2
 
11.1%
2
 
11.1%
K1
 
5.6%
r1
 
5.6%
a1
 
5.6%
,1
 
5.6%
R1
 
5.6%
p1
 
5.6%
u1
 
5.6%
Other values (5)5
27.8%

_embedded.show.dvdCountry.code
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing114
Missing (%)99.1%
Memory size1.0 KiB
KR

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowKR

Common Values

ValueCountFrequency (%)
KR1
 
0.9%
(Missing)114
99.1%

Length

2022-09-05T21:48:14.469325image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:48:14.552273image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
kr1
100.0%

Most occurring characters

ValueCountFrequency (%)
K1
50.0%
R1
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter2
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K1
50.0%
R1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
K1
50.0%
R1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
K1
50.0%
R1
50.0%

_embedded.show.dvdCountry.timezone
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing114
Missing (%)99.1%
Memory size1.0 KiB
Asia/Seoul

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters10
Distinct characters10
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowAsia/Seoul

Common Values

ValueCountFrequency (%)
Asia/Seoul1
 
0.9%
(Missing)114
99.1%

Length

2022-09-05T21:48:14.629195image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:48:14.718724image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
asia/seoul1
100.0%

Most occurring characters

ValueCountFrequency (%)
A1
10.0%
s1
10.0%
i1
10.0%
a1
10.0%
/1
10.0%
S1
10.0%
e1
10.0%
o1
10.0%
u1
10.0%
l1
10.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7
70.0%
Uppercase Letter2
 
20.0%
Other Punctuation1
 
10.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s1
14.3%
i1
14.3%
a1
14.3%
e1
14.3%
o1
14.3%
u1
14.3%
l1
14.3%
Uppercase Letter
ValueCountFrequency (%)
A1
50.0%
S1
50.0%
Other Punctuation
ValueCountFrequency (%)
/1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin9
90.0%
Common1
 
10.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
A1
11.1%
s1
11.1%
i1
11.1%
a1
11.1%
S1
11.1%
e1
11.1%
o1
11.1%
u1
11.1%
l1
11.1%
Common
ValueCountFrequency (%)
/1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII10
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A1
10.0%
s1
10.0%
i1
10.0%
a1
10.0%
/1
10.0%
S1
10.0%
e1
10.0%
o1
10.0%
u1
10.0%
l1
10.0%

_embedded.show.webChannel
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing115
Missing (%)100.0%
Memory size1.0 KiB

Interactions

2022-09-05T21:48:04.124269image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:53.894485image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:55.096796image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:56.138765image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:57.127049image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:58.149288image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:59.079271image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:59.959228image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:00.827067image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:01.617879image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:02.450519image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:03.286028image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:04.193214image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:54.075123image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:55.193164image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:56.223141image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:57.218021image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:58.226297image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:59.153988image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:00.035468image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:00.894319image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:01.683331image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:02.521052image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:03.357888image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:04.267956image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:54.160155image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:55.290758image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:56.312332image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:57.326336image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:58.308137image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:59.231261image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:00.112201image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:00.956718image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:01.755446image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:02.592563image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:03.432889image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:04.337209image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:54.237212image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:55.374446image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:56.399789image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:57.404138image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:58.391400image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:59.301480image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:00.184466image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:01.020125image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:01.823798image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:02.661570image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:03.503140image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:04.409243image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:54.318756image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:55.465153image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:56.488283image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:57.486286image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:58.470793image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:59.385254image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:00.260129image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:01.091883image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:01.897380image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:02.734209image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:03.573066image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:04.476586image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:54.406035image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:55.550321image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:56.569467image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:57.568070image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:58.548730image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:59.453627image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:00.331458image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:01.153676image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:01.964467image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:02.799542image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:03.640563image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:04.542847image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:54.496061image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:55.645652image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:56.643093image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:57.648957image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:58.624748image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:59.523079image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:00.399512image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:01.218147image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:02.027314image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:02.864916image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:03.706359image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:04.620729image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:54.642108image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:55.746862image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:56.731856image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:57.732866image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:58.708629image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:59.600590image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:00.477887image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:01.284627image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:02.105053image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:02.940615image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:03.778617image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:04.686203image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:54.740931image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:55.819156image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:56.803660image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:57.810107image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:58.778425image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:59.666219image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:00.542169image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:01.352689image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:02.173743image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:03.007735image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:03.844432image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:04.752214image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:54.834099image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:55.899205image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:56.880256image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:57.888267image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:58.855528image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:59.736746image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:00.611516image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:01.419089image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:02.239497image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:03.072622image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:03.912810image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:04.824167image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:54.926697image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:55.972169image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:56.965175image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:57.990708image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:58.929480image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:59.810583image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:00.686954image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:01.483595image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:02.308888image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:03.143428image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:03.985627image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:04.892142image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:55.009711image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:56.056822image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:57.044719image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:58.070072image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:59.003410image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:47:59.886295image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:00.755383image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:01.549324image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:02.377032image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:03.214844image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:48:04.057579image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Correlations

2022-09-05T21:48:14.846352image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-09-05T21:48:15.228784image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-09-05T21:48:15.472049image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-09-05T21:48:15.750249image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-09-05T21:48:05.257424image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-09-05T21:48:05.975524image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-09-05T21:48:06.489144image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

idurlnameseasonnumbertypeairdateairtimeairstampruntimesummaryrating.averageimage.mediumimage.original_links.self.href_embedded.show.id_embedded.show.url_embedded.show.name_embedded.show.type_embedded.show.language_embedded.show.genres_embedded.show.status_embedded.show.runtime_embedded.show.averageRuntime_embedded.show.premiered_embedded.show.ended_embedded.show.officialSite_embedded.show.schedule.time_embedded.show.schedule.days_embedded.show.rating.average_embedded.show.weight_embedded.show.network_embedded.show.webChannel.id_embedded.show.webChannel.name_embedded.show.webChannel.country.name_embedded.show.webChannel.country.code_embedded.show.webChannel.country.timezone_embedded.show.webChannel.officialSite_embedded.show.dvdCountry_embedded.show.externals.tvrage_embedded.show.externals.thetvdb_embedded.show.externals.imdb_embedded.show.image.medium_embedded.show.image.original_embedded.show.summary_embedded.show.updated_embedded.show._links.self.href_embedded.show._links.previousepisode.hrefimage_embedded.show.webChannel.country_embedded.show._links.nextepisode.href_embedded.show.image_embedded.show.network.id_embedded.show.network.name_embedded.show.network.country.name_embedded.show.network.country.code_embedded.show.network.country.timezone_embedded.show.network.officialSite_embedded.show.dvdCountry.name_embedded.show.dvdCountry.code_embedded.show.dvdCountry.timezone_embedded.show.webChannel
01977900https://www.tvmaze.com/episodes/1977900/obycnaa-zensina-2x04-seria-13Серия 1324.0regular2020-12-2410:002020-12-23T22:00:00+00:0054.0NoneNaNhttps://static.tvmaze.com/uploads/images/medium_landscape/290/726674.jpghttps://static.tvmaze.com/uploads/images/original_untouched/290/726674.jpghttps://api.tvmaze.com/episodes/197790039115https://www.tvmaze.com/shows/39115/obycnaa-zensinaОбычная женщинаScriptedRussian[Drama, Crime, Mystery]Ended50.048.02018-10-292021-01-07https://premier.one/show/840522:00[Monday, Tuesday, Wednesday, Thursday]7.739NaN281.0PremierRussian FederationRUAsia/KamchatkaNoneNaNNaN345280.0tt8561620https://static.tvmaze.com/uploads/images/medium_portrait/289/722910.jpghttps://static.tvmaze.com/uploads/images/original_untouched/289/722910.jpg<p>Marina is in her late 30s, she has a successful business and a close-knit family. Her husband is a surgeon and her daughters study at fancy establishments. To everybody her life seems perfect. Though, it is all just a facade concealing the real problems: her husband has a mistress, her elder daughter is a slacker and drug-dealer, her youngest is a sociopath. Well, Marina herself is not really a flower-lady, but a brothel-keeper who is hiding her dark business from everyone. The truth may come out when a girl of Marina's is found dead.</p>1610110841https://api.tvmaze.com/shows/39115https://api.tvmaze.com/episodes/1977905NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
11963999https://www.tvmaze.com/episodes/1963999/257-pricin-ctoby-zit-2x09-seria-22Серия 2229.0regular2020-12-242020-12-24T00:00:00+00:0025.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/196399943722https://www.tvmaze.com/shows/43722/257-pricin-ctoby-zit257 причин, чтобы житьScriptedRussian[Drama, Comedy]EndedNaN24.02020-03-262021-01-21https://start.ru/watch/257-prichin-chtoby-zhit[Thursday]NaN73NaN245.0StartRussian FederationRUAsia/KamchatkaNoneNaNNaN377678.0tt11477416https://static.tvmaze.com/uploads/images/medium_portrait/260/651809.jpghttps://static.tvmaze.com/uploads/images/original_untouched/260/651809.jpg<p>When terminal cancer patient Zhenya unexpectedly receives a clean bill of health, she can't believe it. She's in remission. But then her life implodes. Homeless, unemployed, and newly single - she stumbles across a list she wrote while she was sick of things she wanted to do when she got better. 257 of them - and now she won't give up until she checks off them all!</p>1653640849https://api.tvmaze.com/shows/43722https://api.tvmaze.com/episodes/1964003NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
21949912https://www.tvmaze.com/episodes/1949912/smesariki-novyj-sezon-1x33-zagvozdkaЗагвоздка133.0regular2020-12-242020-12-24T00:00:00+00:006.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/194991248151https://www.tvmaze.com/shows/48151/smesariki-novyj-sezonСмешарики. Новый сезонAnimationRussian[Comedy, Family]Running7.07.02020-05-18Nonehttps://www.kinopoisk.ru/series/1379016/[Thursday]NaN37NaN381.0КиноПоиск HDRussian FederationRUAsia/Kamchatkahttps://hd.kinopoisk.ru/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/257/643435.jpghttps://static.tvmaze.com/uploads/images/original_untouched/257/643435.jpg<p>Stories about friendship and adventures of charming round heroes. Fun and musical, unexpected and dreamy, homely and adventurous. The whole world in one cozy chamomile valley.</p>1646904606https://api.tvmaze.com/shows/48151https://api.tvmaze.com/episodes/2164183NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
31949913https://www.tvmaze.com/episodes/1949913/smesariki-novyj-sezon-1x34-starinnyj-novogodnij-obycajСтаринный новогодний обычай134.0regular2020-12-242020-12-24T00:00:00+00:006.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/194991348151https://www.tvmaze.com/shows/48151/smesariki-novyj-sezonСмешарики. Новый сезонAnimationRussian[Comedy, Family]Running7.07.02020-05-18Nonehttps://www.kinopoisk.ru/series/1379016/[Thursday]NaN37NaN381.0КиноПоиск HDRussian FederationRUAsia/Kamchatkahttps://hd.kinopoisk.ru/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/257/643435.jpghttps://static.tvmaze.com/uploads/images/original_untouched/257/643435.jpg<p>Stories about friendship and adventures of charming round heroes. Fun and musical, unexpected and dreamy, homely and adventurous. The whole world in one cozy chamomile valley.</p>1646904606https://api.tvmaze.com/shows/48151https://api.tvmaze.com/episodes/2164183NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
41960733https://www.tvmaze.com/episodes/1960733/psih-1x08-vozrozdenieВозрождение18.0regular2020-12-2412:002020-12-24T00:00:00+00:0070.0NoneNaNhttps://static.tvmaze.com/uploads/images/medium_landscape/301/752694.jpghttps://static.tvmaze.com/uploads/images/original_untouched/301/752694.jpghttps://api.tvmaze.com/episodes/196073349280https://www.tvmaze.com/shows/49280/psihПсихScriptedRussian[Drama, Thriller]Ended62.062.02020-11-052020-12-24https://more.tv/psih[Thursday]NaN27NaN246.0more.tvRussian FederationRUAsia/KamchatkaNoneNaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/295/739859.jpghttps://static.tvmaze.com/uploads/images/original_untouched/295/739859.jpg<p>Oleg is a metropolitan psychotherapist. Clients of the central district of Moscow line up to him. Only lately Oleg doesn't like them, he tolerates them. Midlife crisis, life with mom at 40, loss of self-esteem, drug addiction, irritability and growing aggression. None of the clients are aware of his problems. From the outside, he seems successful, happily married, wealthy. Nobody knows the truth.</p><p> </p><p>A year ago, his wife went missing. She has been gone for 384 days.</p>1653851744https://api.tvmaze.com/shows/49280https://api.tvmaze.com/episodes/1960733NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
51982409https://www.tvmaze.com/episodes/1982409/volk-1x11-seria-11Серия 11111.0regular2020-12-242020-12-24T00:00:00+00:0051.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/198240952181https://www.tvmaze.com/shows/52181/volkВолкScriptedRussian[Drama, Adventure, Mystery]Ended51.050.02020-12-072020-12-28https://premier.one/show/12339[Monday, Thursday]NaN24NaN281.0PremierRussian FederationRUAsia/KamchatkaNoneNaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/287/718741.jpghttps://static.tvmaze.com/uploads/images/original_untouched/287/718741.jpgNone1640435531https://api.tvmaze.com/shows/52181https://api.tvmaze.com/episodes/1982412NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
61982410https://www.tvmaze.com/episodes/1982410/volk-1x12-seria-12Серия 12112.0regular2020-12-242020-12-24T00:00:00+00:0051.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/198241052181https://www.tvmaze.com/shows/52181/volkВолкScriptedRussian[Drama, Adventure, Mystery]Ended51.050.02020-12-072020-12-28https://premier.one/show/12339[Monday, Thursday]NaN24NaN281.0PremierRussian FederationRUAsia/KamchatkaNoneNaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/287/718741.jpghttps://static.tvmaze.com/uploads/images/original_untouched/287/718741.jpgNone1640435531https://api.tvmaze.com/shows/52181https://api.tvmaze.com/episodes/1982412NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
71987502https://www.tvmaze.com/episodes/1987502/passaziry-1x01-svetlana-i-igorСветлана и Игорь11.0regular2020-12-242020-12-24T00:00:00+00:0021.0NoneNaNhttps://static.tvmaze.com/uploads/images/medium_landscape/375/939994.jpghttps://static.tvmaze.com/uploads/images/original_untouched/375/939994.jpghttps://api.tvmaze.com/episodes/198750252499https://www.tvmaze.com/shows/52499/passaziryПассажирыScriptedRussian[Drama, Supernatural]EndedNaN23.02020-12-242022-05-27https://start.ru/watch/passazhiry[Friday]NaN82NaN245.0StartRussian FederationRUAsia/KamchatkaNoneNaNNaN393530.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/394/986714.jpghttps://static.tvmaze.com/uploads/images/original_untouched/394/986714.jpgNone1661864044https://api.tvmaze.com/shows/52499https://api.tvmaze.com/episodes/2270905NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
81987720https://www.tvmaze.com/episodes/1987720/passaziry-1x02-saskaСашка12.0regular2020-12-242020-12-24T00:00:00+00:0022.0NoneNaNhttps://static.tvmaze.com/uploads/images/medium_landscape/291/728563.jpghttps://static.tvmaze.com/uploads/images/original_untouched/291/728563.jpghttps://api.tvmaze.com/episodes/198772052499https://www.tvmaze.com/shows/52499/passaziryПассажирыScriptedRussian[Drama, Supernatural]EndedNaN23.02020-12-242022-05-27https://start.ru/watch/passazhiry[Friday]NaN82NaN245.0StartRussian FederationRUAsia/KamchatkaNoneNaNNaN393530.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/394/986714.jpghttps://static.tvmaze.com/uploads/images/original_untouched/394/986714.jpgNone1661864044https://api.tvmaze.com/shows/52499https://api.tvmaze.com/episodes/2270905NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
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1051974796https://www.tvmaze.com/episodes/1974796/summer-camp-island-3x08-yeti-confetti-chapter-1-dont-tell-lucyYeti Confetti Chapter 1: Don't Tell Lucy38.0regular2020-12-242020-12-24T17:00:00+00:0012.0<p>Oscar has to distract Lucy while the Yetis prepare a surprise for her.</p>NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/290/726729.jpghttps://static.tvmaze.com/uploads/images/original_untouched/290/726729.jpghttps://api.tvmaze.com/episodes/197479626643https://www.tvmaze.com/shows/26643/summer-camp-islandSummer Camp IslandAnimationEnglish[Comedy, Adventure, Fantasy]To Be DeterminedNaN11.02018-07-07Nonehttps://play.hbomax.com/series/urn:hbo:series:GXkyDLAgeBY7CZgEAACHO[]5.485NaN329.0HBO MaxNaNNaNNaNhttps://www.hbomax.com/NaNNaN338738.0tt8146760https://static.tvmaze.com/uploads/images/medium_portrait/382/956804.jpghttps://static.tvmaze.com/uploads/images/original_untouched/382/956804.jpg<p>Set in a world of anthropomorphic animals, Summer Camp Island follows two best friends Oscar, and Hedgehog, and Oscar who are dropped off at a surreal summer camp. The camp is a host to many odd occurrences such as: camp counselors who are composed of popular girls who know magic, horses that transform into unicorns, talking sharks, post-it notes that lead to other dimensions and nosy monsters that live under the bed. Oscar and Hedgehog must contend with these out of place events and make their stay at camp worthwhile.</p>1639300202https://api.tvmaze.com/shows/26643https://api.tvmaze.com/episodes/2234373NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
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1071974798https://www.tvmaze.com/episodes/1974798/summer-camp-island-3x10-yeti-confetti-chapter-3-the-sherbet-scoopYeti Confetti Chapter 3: The Sherbet Scoop310.0regular2020-12-242020-12-24T17:00:00+00:0012.0<p>Lucy decides to tell a story during a Yeti cloud-making ceremony about a Yeti Elder she doesn't know.</p>NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/290/726731.jpghttps://static.tvmaze.com/uploads/images/original_untouched/290/726731.jpghttps://api.tvmaze.com/episodes/197479826643https://www.tvmaze.com/shows/26643/summer-camp-islandSummer Camp IslandAnimationEnglish[Comedy, Adventure, Fantasy]To Be DeterminedNaN11.02018-07-07Nonehttps://play.hbomax.com/series/urn:hbo:series:GXkyDLAgeBY7CZgEAACHO[]5.485NaN329.0HBO MaxNaNNaNNaNhttps://www.hbomax.com/NaNNaN338738.0tt8146760https://static.tvmaze.com/uploads/images/medium_portrait/382/956804.jpghttps://static.tvmaze.com/uploads/images/original_untouched/382/956804.jpg<p>Set in a world of anthropomorphic animals, Summer Camp Island follows two best friends Oscar, and Hedgehog, and Oscar who are dropped off at a surreal summer camp. The camp is a host to many odd occurrences such as: camp counselors who are composed of popular girls who know magic, horses that transform into unicorns, talking sharks, post-it notes that lead to other dimensions and nosy monsters that live under the bed. Oscar and Hedgehog must contend with these out of place events and make their stay at camp worthwhile.</p>1639300202https://api.tvmaze.com/shows/26643https://api.tvmaze.com/episodes/2234373NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
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1111950702https://www.tvmaze.com/episodes/1950702/texas-6-1x07-the-rematchThe Rematch17.0regular2020-12-242020-12-24T17:00:00+00:0033.0<p>Strawn gets a do-over as they face off against Gordon for the state quarterfinals, with a healthy J.W. and Marco ready to make the most of their senior-year season.</p>NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/290/726712.jpghttps://static.tvmaze.com/uploads/images/original_untouched/290/726712.jpghttps://api.tvmaze.com/episodes/195070251316https://www.tvmaze.com/shows/51316/texas-6Texas 6DocumentaryEnglish[Sports]RunningNaN36.02020-11-26Nonehttps://www.cbs.com/shows/texas-6/[]NaN46NaN107.0Paramount+NaNNaNNaNhttps://www.paramountplus.com/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/282/706759.jpghttps://static.tvmaze.com/uploads/images/original_untouched/282/706759.jpg<p><b>Texas 6</b> takes place in Strawn, Texas and follows the Greyhounds, a high school six-man football team under the direction of Coach Dewaine Lee, as they attempt a three-peat for the 6-Man Football State Championship. While football remains the spine of Strawn, <i>Texas 6</i> ultimately depicts the spirit of a small town and a team that shows up for one another on and off the field.</p>1637773188https://api.tvmaze.com/shows/51316https://api.tvmaze.com/episodes/2188850NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
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1141976648https://www.tvmaze.com/episodes/1976648/wwe-nxt-uk-2020-12-24-episode-52Episode 52202052.0regular2020-12-2415:002020-12-24T20:00:00+00:0060.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/197664839053https://www.tvmaze.com/shows/39053/wwe-nxt-ukWWE NXT UKSportsEnglish[]Running60.060.02018-10-17NoneNone15:00[Thursday]NaN87NaN15.0WWE NetworkUnited StatesUSAmerica/New_YorkNoneNaNNaN354295.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/401/1002870.jpghttps://static.tvmaze.com/uploads/images/original_untouched/401/1002870.jpg<p>The one-hour episodes will feature the biggest names from NXT UK, including Pete Dunne, Mark Andrews, Rhea Ripley, Toni Storm, Tyler Bate, Trent Seven and Wolfgang. Joining the NXT UK broadcasting team as backstage interviewer is British broadcasting personality Radzi Chinyanganya, best known for hosting ITV game show "Cannonball," and in his ongoing role as a presenter of the world's longest-running children's TV show, the BBC's "Blue Peter." Calling the action are commentators Nigel McGuinness and Vic Joseph, joined by ring announcer Andy Shepherd and NXT UK General Manager, the legendary Johnny Saint.</p>1661770465https://api.tvmaze.com/shows/39053https://api.tvmaze.com/episodes/2375913NaNNaNhttps://api.tvmaze.com/episodes/2382043NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN